Senior Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Senior Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
11/02/2026
Full time
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
11/02/2026
Full time
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Senior Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
11/02/2026
Full time
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
11/02/2026
Full time
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
11/02/2026
Full time
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Principal Mobile Application Developer About the Role At SharkNinja, we create intelligent, connected products that delight consumers and disrupt categories. We are building systems that integrate hardware, software, and digital experiences using AI-driven processes to help accelerate design, coding, and testing. This is a senior individual-contributor role with full ownership of the mobile app's architecture and the support of new products as they come to the app. You will own the architecture behind how SharkNinja products come to life in the app - the feature architecture, the device experiences, the connectivity flows, and the consumer-facing quality of what is built on it - and partner with product teams to bring new products onto it. You are the technical decision-maker for the app's architecture: you decide how it is built, you set the standards it is held to, and you are accountable for how it performs in real consumers' homes. You will also establish and document engineering patterns and best practices in coordination with the App Architect, so the way we build is consistent, repeatable, and easy to adopt across products. Together, we're making our products feel smarter every day they're in the home. What You'll Do Own the mobile app architecture that new products are built on - feature architecture, device experiences, pairing and provisioning flows, and consumer-facing behavior from first launch through steady state. Make the architecture and technology decisions for the mobile app, and remain deeply hands-on building in React Native, Expo, and TypeScript. Own how new products enter the app through our capability-based device definitions - declaring what a product is and what it can do, so screens compose from capabilities rather than per-product special cases. Serve as the mobile technical authority for onboarding and supporting new products, working with embedded, cloud, hardware, and product partners to define how a new device behaves in the app and to drive the tradeoffs that surface during development. Define the reusable components, patterns, and libraries needed to deliver these experiences, and decide what gets built, refactored, or replaced - extending our layered component library and semantic theming system rather than accumulating one-off UI. Establish, document, and own engineering patterns and best practices for the mobile app in coordination with the App Architect, and drive their adoption across teams so products are built consistently. Own quality end to end: test and automation strategy, crash and performance targets, staged rollout, and the field issues that come back from real homes. Lead the hardest technical problems personally - BLE and WiFi connectivity reliability, versioned device protocols, real-time state over WebSocket, and the bugs that only reproduce on real hardware. Lead technical research and proof-of-concept validation, running pre-research and building prototypes to de-risk major architectural decisions before committing to full-scale production. Mentor mid-level and senior engineers through design review, code review, and pairing, and grow their ability to own features independently. Collaborate across regions with distributed global teams, including the UK and China, to align technical roadmaps, share patterns, and keep delivery coordinated across time zones. Champion AI-assisted workflows and build AI skills across the broader engineering team through shared practices, tooling, and coaching, going beyond personal tool use. Write the design docs for significant features, drive the decisions to closure, and be accountable for how they hold up in production. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree welcome but not required. 8+ years of software engineering experience, with deep expertise in React Native and TypeScript for iOS and Android at consumer scale. A track record of owning the architecture of a mobile app used by large numbers of consumers, from design through launch and long-term support. Demonstrated technical leadership - you set technical direction, bring others along through design and code review, and are trusted as the decision-maker within your scope. Strong understanding of full-stack system architecture and mobile-to-cloud integration patterns, including API contract design, client-side caching and cache invalidation, real-time state synchronization, and failure and retry behavior across unreliable connections. Fluency with the mobile toolchain and release pipeline: Xcode, Android Studio, Git, Gradle, CocoaPods, Swift Package Manager, CI/CD, staged rollout, and production diagnostics. Native depth in Swift and/or Kotlin sufficient to debug across the bridge and implement platform-specific behavior when a product needs it. Sound judgment about when to build, reuse, or replace - and the discipline to leave the code well documented and understood. A passion for creating consumer-friendly, connected product experiences. Curiosity, adaptability, and a drive to be part of an A-Player engineering team. Preferred Qualifications Depth in the Expo ecosystem - Expo Router and typed routes, config plugins, custom native modules - plus TanStack Query, Reanimated, and Xcode/Android Studio build systems. Experience with binary protocol work: parsing and versioning device payloads, and evolving a protocol without breaking already-shipped firmware. Substantial experience with connected devices, IoT ecosystems, or device-to-app connectivity in production. Hands-on experience with BLE (Bluetooth Low Energy) and WiFi provisioning, including the failure modes that only appear in real homes. Experience with Rust, C/C++, or other systems programming languages, and comfort working alongside firmware teams. Background in robotics, consumer electronics, or smart home products. Experience launching a new hardware product's app experience from zero to shipped. Experience using AI-assisted development tools to accelerate design, coding, and testing without sacrificing quality. What Success Looks Like New products are onboarded to the app on schedule, with app experiences that hold up in real consumers' homes. Quality metrics - crash-free sessions, connectivity success rates, performance - are instrumented and trending in the right direction. The architecture you own is coherent and maintainable, and new products and features land faster because of the foundations you put in place. Engineers around you are making stronger design decisions without needing you in every review. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $190,000-$210,000 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA . click apply for full job details
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/02/2026
Full time
Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
This job is with Avaloq, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Company Description Founded and headquartered in Switzerland, Avaloq is continuously expanding its global footprint with around 2,500 colleagues in 12 countries, and more than 170 clients in 35 countries. We are an industry-leading provider of wealth management technology and services for financial institutions around the world, including private banks and wealth managers, investment managers, as well as retail and neo banks. Our research led approach and continual innovation is powered by the passion and creativity of our colleagues. We are always looking for talented people to join us on our mission to orchestrate the financial ecosystem and democratize access to wealth management. Avaloq offers the opportunity to work closely with some of the world's leading financial institutions as we jointly develop and shape careers. Championing a collaborative, supportive and flexible work environment empowers our colleagues to reach their full potential. Job Description Avaloq's R&D Lab is building a SaaS, API-first, composable banking platform. You will help develop its Rust backend, creating financial technology where precision, quality and scalability matter, while working closely with engineers in Fort Lauderdale and Zurich. These 3 roles are among the first engineering roles at our new Fort Lauderdale development center, offering significant scope for ownership as the team grows. You will work directly with clients, see how your solutions are used and bring those insights back into the product. The role includes onboarding with the Zurich team, collaborative mornings and productive afternoons, with regular travel to Switzerland and occasional travel to client sites. Our stack Rust with Tokio and the AWS SDK for Rust. Serverless-first on AWS, using Lambda, DynamoDB, SQS and S3, with GitHub Actions for CI/CD. Clients integrate through our APIs and the Model Context Protocol (MCP). We do not run containers. Useful domain experience Depending on the role, relevant experience may include wealth and asset management, discretionary portfolio management, investment performance and attribution, portfolio valuation and rebalancing, benchmarks and fees, or US investment taxation, including tax lots, cost basis, holding periods, wash sales, corporate actions, withholding and tax reporting. What you'll do: Design, develop and test Rust backend services for complex financial products, with a focus on accuracy, scalability and reliability. Translate complex financial rules and mathematical concepts into precise, efficient and testable software, accounting for numerical precision and edge cases. Build scalable solutions using historized, non-relational data models and asynchronous, event-driven architectures. Contribute to technical specifications, design discussions and code reviews, using AI coding agents while maintaining rigorous review standards and accountability. Own features through the development lifecycle, from implementation and automated testing to deployment and monitoring, working alongside Platform and SRE engineers. Work directly with clients and domain specialists to analyse product questions, solve problems and bring insights back into product development. Qualifications Strong programming foundations in a statically typed language such as Rust, C++, Java, Scala, Kotlin, C#, Go or TypeScript. Master's degree or PhD in computer science, mathematics, physics or a related quantitative field. Strong modelling skills, including experience or understanding of historized data, effective dating, immutability and audit trails. Strong analytical ability and intellectual curiosity, with the ability to quickly learn new technologies and complex financial domains. Clear and confident communication skills, with the ability to explain technical concepts effectively to both technical and business audiences. Ability to work independently within a distributed team and travel to Switzerland and client sites when required. It would be a real bonus if you have: Production Rust experience, or experience with another systems/strongly typed language such as C++, Haskell, OCaml or Scala. Experience in wealth or asset management technology, including investment performance, portfolio construction/rebalancing, or tax, accounting and other rule-heavy financial software. Experience with AWS serverless and event-driven architecture, particularly Lambda, DynamoDB, SQS, S3 and API Gateway, or related distributed-systems technologies. Experience with AI-assisted engineering, client-facing product development, research or open-source software. Additional Information This role includes onboarding with the existing team in Zurich, regular travel to Switzerland and occasional travel to client sites. We realize that managing work life balance is a challenge we all face in our daily lives and in order to support with this we are pleased to offer hybrid and flexible working for most of our Avaloqers to maintain work life balance and still continue our fantastic Avaloq culture in our global offices. In Avaloq we are proud to embrace diversity and understand the success of our business is built on the power of different opinions, we are whole heartedly committed to fostering an equal opportunity environment and inclusive culture where you can be your true authentic self. We hire, compensate and promote regardless of origin, age, gender identity, sexual orientation or any other fantastic traits that make us all unique, we have done our best to write this advert in an inclusive and neutral way. Please be aware that we will not accept speculative CV submissions for any of our roles from recruitment agencies, and any unsolicited candidate submissions will be exempt from any payment expectations.
10/27/2026
Full time
This job is with Avaloq, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Company Description Founded and headquartered in Switzerland, Avaloq is continuously expanding its global footprint with around 2,500 colleagues in 12 countries, and more than 170 clients in 35 countries. We are an industry-leading provider of wealth management technology and services for financial institutions around the world, including private banks and wealth managers, investment managers, as well as retail and neo banks. Our research led approach and continual innovation is powered by the passion and creativity of our colleagues. We are always looking for talented people to join us on our mission to orchestrate the financial ecosystem and democratize access to wealth management. Avaloq offers the opportunity to work closely with some of the world's leading financial institutions as we jointly develop and shape careers. Championing a collaborative, supportive and flexible work environment empowers our colleagues to reach their full potential. Job Description Avaloq's R&D Lab is building a SaaS, API-first, composable banking platform. You will help develop its Rust backend, creating financial technology where precision, quality and scalability matter, while working closely with engineers in Fort Lauderdale and Zurich. These 3 roles are among the first engineering roles at our new Fort Lauderdale development center, offering significant scope for ownership as the team grows. You will work directly with clients, see how your solutions are used and bring those insights back into the product. The role includes onboarding with the Zurich team, collaborative mornings and productive afternoons, with regular travel to Switzerland and occasional travel to client sites. Our stack Rust with Tokio and the AWS SDK for Rust. Serverless-first on AWS, using Lambda, DynamoDB, SQS and S3, with GitHub Actions for CI/CD. Clients integrate through our APIs and the Model Context Protocol (MCP). We do not run containers. Useful domain experience Depending on the role, relevant experience may include wealth and asset management, discretionary portfolio management, investment performance and attribution, portfolio valuation and rebalancing, benchmarks and fees, or US investment taxation, including tax lots, cost basis, holding periods, wash sales, corporate actions, withholding and tax reporting. What you'll do: Design, develop and test Rust backend services for complex financial products, with a focus on accuracy, scalability and reliability. Translate complex financial rules and mathematical concepts into precise, efficient and testable software, accounting for numerical precision and edge cases. Build scalable solutions using historized, non-relational data models and asynchronous, event-driven architectures. Contribute to technical specifications, design discussions and code reviews, using AI coding agents while maintaining rigorous review standards and accountability. Own features through the development lifecycle, from implementation and automated testing to deployment and monitoring, working alongside Platform and SRE engineers. Work directly with clients and domain specialists to analyse product questions, solve problems and bring insights back into product development. Qualifications Strong programming foundations in a statically typed language such as Rust, C++, Java, Scala, Kotlin, C#, Go or TypeScript. Master's degree or PhD in computer science, mathematics, physics or a related quantitative field. Strong modelling skills, including experience or understanding of historized data, effective dating, immutability and audit trails. Strong analytical ability and intellectual curiosity, with the ability to quickly learn new technologies and complex financial domains. Clear and confident communication skills, with the ability to explain technical concepts effectively to both technical and business audiences. Ability to work independently within a distributed team and travel to Switzerland and client sites when required. It would be a real bonus if you have: Production Rust experience, or experience with another systems/strongly typed language such as C++, Haskell, OCaml or Scala. Experience in wealth or asset management technology, including investment performance, portfolio construction/rebalancing, or tax, accounting and other rule-heavy financial software. Experience with AWS serverless and event-driven architecture, particularly Lambda, DynamoDB, SQS, S3 and API Gateway, or related distributed-systems technologies. Experience with AI-assisted engineering, client-facing product development, research or open-source software. Additional Information This role includes onboarding with the existing team in Zurich, regular travel to Switzerland and occasional travel to client sites. We realize that managing work life balance is a challenge we all face in our daily lives and in order to support with this we are pleased to offer hybrid and flexible working for most of our Avaloqers to maintain work life balance and still continue our fantastic Avaloq culture in our global offices. In Avaloq we are proud to embrace diversity and understand the success of our business is built on the power of different opinions, we are whole heartedly committed to fostering an equal opportunity environment and inclusive culture where you can be your true authentic self. We hire, compensate and promote regardless of origin, age, gender identity, sexual orientation or any other fantastic traits that make us all unique, we have done our best to write this advert in an inclusive and neutral way. Please be aware that we will not accept speculative CV submissions for any of our roles from recruitment agencies, and any unsolicited candidate submissions will be exempt from any payment expectations.