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).
09/23/2026
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).
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services 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 Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms 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: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI 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).
09/23/2026
Full time
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services 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 Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms 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: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI 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 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).
09/23/2026
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).
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).
09/23/2026
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).
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services 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 Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms 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: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI 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).
09/23/2026
Full time
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation 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 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 4 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 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services 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 Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms 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: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI 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).
Gravitee is a 2025 Gartner Magic Quadrant Leader , on a mission to govern the world's intelligence . We deliver the industry's most advanced platform for Any API, Any Event, and Any AI Agent , trusted by global leaders like Michelin, Roche, and Blue Yonder. Why join us? The Mission : We are the first to bridge traditional API Management with the new frontier of AI Agent Security The Momentum : A high-growth Leader - combining market credibility with startup speed The DNA : We hire people who Hold Nothing Back - passionate builders who want to redefine digital infrastructure Don't just watch the AI revolution. Build the infrastructure that controls and secures it. The Role We are looking for a Senior Software Engineer to build and maintain the identity and authorization features of Gravitee Access Management (AM) - across the AM runtime and the access-management experience in Gamma, Gravitee's next generation product surface. This is a new role. Today, AM engineering is based entirely in Europe. This hire establishes US-hours ownership of Level 3 and Level 4 authentication and authorization incidents, and adds delivery capacity toward AM parity in Gamma - part of building sustainable L3/L4 engineering capability in the US. You will split your time roughly 80% feature delivery and 20% L3/L4 support and bug fixing (it varies week to week), working as an embedded member of the AM team, which is based in Europe. What You Will Be Doing In this role, you will: Design and deliver features end to end, from discovery and technical design through implementation, testing, release, and iteration. Build and maintain identity and authorization features of Gravitee Access Management, across the AM runtime and the AM experience in Gamma. Implement and support OAuth 2.0 and OIDC flows (authorization code + PKCE, client credentials, token exchange), SAML 2.0 as both IdP and SP, SCIM, and FAPI/CIBA/UMA profiles. Work with token and session semantics - JWT, JWKS, key rotation, revocation, introspection, MFA and step-up, WebAuthn/FIDO2, and IdP federation and social login. Keep security behavior and upgrades safe: standards compliance, secure defaults, certificate and secret handling, consent, audit logs, and defenses against token replay, SSRF, and account takeover. Own safe migrations and backward compatibility across MongoDB and JDBC, and support multi-domain, multi-region deployments and login/token endpoint performance. Own US-hours Level 3 and Level 4 escalations for AM customers as part of the L3 pager duty rotation. Use LLMs and AI-assisted development tools thoughtfully for prototyping, implementation, testing, debugging, and exploration, applying sound engineering judgment to validate AI-generated work. Write meaningful automated tests and contribute to reliable delivery practices. • Collaborate with product managers, designers, engineers, and technical leaders - including the AM team based in Europe - to discover effective solutions and improve them through code and design reviews. Share what you learn and help the team make practical choices as identity standards and protocols evolve. Essential Skills We are looking for evidence that you can succeed in the role, whether gained through employment, open-source work, or equivalent practical experience: 5+ years building and running production backend software, on a team that ships and supports its own product; you have personally resolved production incidents. Strong Java experience (C# accepted if the object-oriented depth is there), with Maven and a reactive stack such as Vert.x/RxJava. Deep working knowledge of identity standards: OAuth 2.0 and OIDC flows (authorization code + PKCE, client credentials, token exchange), SAML 2.0, SCIM, and FAPI/CIBA/UMA profiles. • Solid grasp of token and session semantics: JWT, JWKS, rotation, revocation, introspection, MFA/step-up, WebAuthn/FIDO2, and IdP federation. A security-first mindset: secure defaults, certificate and secret handling, audit logging, and awareness of token replay, SSRF, and account-takeover risks. Experience with safe migrations and backward compatibility across persistent data stores such as MongoDB or JDBCbacked relational databases. Git-based workflow, code review, and writing your own automated tests. Hands-on experience using LLMs or AI coding assistants as part of an engineering workflow, combined with the judgment to review and improve their output. Clear communication, collaborative problem-solving, and the ability to take an ambiguous problem through to production. Desired Skills You do not need to match every item. We would be especially interested in experience with: • Experience at an API gateway, proxy, or service-mesh vendor, or on the API platform team of a large company (e.g., Kong, Google Apigee, MuleSoft, Tyk, Solo.io, Traefik, WSO2). Kubernetes operators and CRDs; OpenAPI tooling; service mesh or Envoy experience. Docker, Kubernetes, and cloud-native application delivery. Model Context Protocol (MCP), Agent2Agent (A2A), tool calling, LLM proxies, or other emerging AI protocols and standards. Prior production experience is not required. Building or operating LLM-powered applications, RAG systems, or agentic workflows - especially their security, governance, and observability needs. Open-source software or enterprise developer platforms. Who Thrives at Gravitee Our growth is powered by people who bring passion to what they build, professionalism to how they work, and a commitment to doing things well. You will thrive here if you: • Bring energy and a constructive attitude to the team. • Adapt quickly and enjoy learning unfamiliar technologies and domains. • Take ownership, communicate clearly, and follow through with urgency. • Balance delivery speed with thoughtful engineering judgment. • Start with the customer problem and care about the quality of the experience you create. • Enjoy working in a fast-moving, collaborative, international environment. Life at Gravitee At Gravitee, we invest in humans, not just roles. You'll get: • Salary of $160,000 • Competitive medical coverage. • Pension / 401(k) program options. • Stock options - you build it, you own it. • 25 days of holiday plus in-country national holidays. • Three mental health days and a wellness allowance. • Your birthday off. • A professional development budget to support your growth. • A hybrid work culture with hubs across regions. • Quarterly team events and an annual company offsite. • A collaborative, international company culture. • Opportunities to grow your scope and career as Gravitee grows. At Gravitee, we believe diverse perspectives make better products and stronger teams. No employee or applicant will be treated less favorably on the grounds of sex, marital status, race, color, nationality, ethnic or national origin, disability, gender, sexual orientation, gender identity, age, pregnancy or maternity, marital or civil partner status, religion, or belief. By applying, you consent to Gravitee storing and processing the personal information you submit as part of the recruitment process.
09/23/2026
Full time
Gravitee is a 2025 Gartner Magic Quadrant Leader , on a mission to govern the world's intelligence . We deliver the industry's most advanced platform for Any API, Any Event, and Any AI Agent , trusted by global leaders like Michelin, Roche, and Blue Yonder. Why join us? The Mission : We are the first to bridge traditional API Management with the new frontier of AI Agent Security The Momentum : A high-growth Leader - combining market credibility with startup speed The DNA : We hire people who Hold Nothing Back - passionate builders who want to redefine digital infrastructure Don't just watch the AI revolution. Build the infrastructure that controls and secures it. The Role We are looking for a Senior Software Engineer to build and maintain the identity and authorization features of Gravitee Access Management (AM) - across the AM runtime and the access-management experience in Gamma, Gravitee's next generation product surface. This is a new role. Today, AM engineering is based entirely in Europe. This hire establishes US-hours ownership of Level 3 and Level 4 authentication and authorization incidents, and adds delivery capacity toward AM parity in Gamma - part of building sustainable L3/L4 engineering capability in the US. You will split your time roughly 80% feature delivery and 20% L3/L4 support and bug fixing (it varies week to week), working as an embedded member of the AM team, which is based in Europe. What You Will Be Doing In this role, you will: Design and deliver features end to end, from discovery and technical design through implementation, testing, release, and iteration. Build and maintain identity and authorization features of Gravitee Access Management, across the AM runtime and the AM experience in Gamma. Implement and support OAuth 2.0 and OIDC flows (authorization code + PKCE, client credentials, token exchange), SAML 2.0 as both IdP and SP, SCIM, and FAPI/CIBA/UMA profiles. Work with token and session semantics - JWT, JWKS, key rotation, revocation, introspection, MFA and step-up, WebAuthn/FIDO2, and IdP federation and social login. Keep security behavior and upgrades safe: standards compliance, secure defaults, certificate and secret handling, consent, audit logs, and defenses against token replay, SSRF, and account takeover. Own safe migrations and backward compatibility across MongoDB and JDBC, and support multi-domain, multi-region deployments and login/token endpoint performance. Own US-hours Level 3 and Level 4 escalations for AM customers as part of the L3 pager duty rotation. Use LLMs and AI-assisted development tools thoughtfully for prototyping, implementation, testing, debugging, and exploration, applying sound engineering judgment to validate AI-generated work. Write meaningful automated tests and contribute to reliable delivery practices. • Collaborate with product managers, designers, engineers, and technical leaders - including the AM team based in Europe - to discover effective solutions and improve them through code and design reviews. Share what you learn and help the team make practical choices as identity standards and protocols evolve. Essential Skills We are looking for evidence that you can succeed in the role, whether gained through employment, open-source work, or equivalent practical experience: 5+ years building and running production backend software, on a team that ships and supports its own product; you have personally resolved production incidents. Strong Java experience (C# accepted if the object-oriented depth is there), with Maven and a reactive stack such as Vert.x/RxJava. Deep working knowledge of identity standards: OAuth 2.0 and OIDC flows (authorization code + PKCE, client credentials, token exchange), SAML 2.0, SCIM, and FAPI/CIBA/UMA profiles. • Solid grasp of token and session semantics: JWT, JWKS, rotation, revocation, introspection, MFA/step-up, WebAuthn/FIDO2, and IdP federation. A security-first mindset: secure defaults, certificate and secret handling, audit logging, and awareness of token replay, SSRF, and account-takeover risks. Experience with safe migrations and backward compatibility across persistent data stores such as MongoDB or JDBCbacked relational databases. Git-based workflow, code review, and writing your own automated tests. Hands-on experience using LLMs or AI coding assistants as part of an engineering workflow, combined with the judgment to review and improve their output. Clear communication, collaborative problem-solving, and the ability to take an ambiguous problem through to production. Desired Skills You do not need to match every item. We would be especially interested in experience with: • Experience at an API gateway, proxy, or service-mesh vendor, or on the API platform team of a large company (e.g., Kong, Google Apigee, MuleSoft, Tyk, Solo.io, Traefik, WSO2). Kubernetes operators and CRDs; OpenAPI tooling; service mesh or Envoy experience. Docker, Kubernetes, and cloud-native application delivery. Model Context Protocol (MCP), Agent2Agent (A2A), tool calling, LLM proxies, or other emerging AI protocols and standards. Prior production experience is not required. Building or operating LLM-powered applications, RAG systems, or agentic workflows - especially their security, governance, and observability needs. Open-source software or enterprise developer platforms. Who Thrives at Gravitee Our growth is powered by people who bring passion to what they build, professionalism to how they work, and a commitment to doing things well. You will thrive here if you: • Bring energy and a constructive attitude to the team. • Adapt quickly and enjoy learning unfamiliar technologies and domains. • Take ownership, communicate clearly, and follow through with urgency. • Balance delivery speed with thoughtful engineering judgment. • Start with the customer problem and care about the quality of the experience you create. • Enjoy working in a fast-moving, collaborative, international environment. Life at Gravitee At Gravitee, we invest in humans, not just roles. You'll get: • Salary of $160,000 • Competitive medical coverage. • Pension / 401(k) program options. • Stock options - you build it, you own it. • 25 days of holiday plus in-country national holidays. • Three mental health days and a wellness allowance. • Your birthday off. • A professional development budget to support your growth. • A hybrid work culture with hubs across regions. • Quarterly team events and an annual company offsite. • A collaborative, international company culture. • Opportunities to grow your scope and career as Gravitee grows. At Gravitee, we believe diverse perspectives make better products and stronger teams. No employee or applicant will be treated less favorably on the grounds of sex, marital status, race, color, nationality, ethnic or national origin, disability, gender, sexual orientation, gender identity, age, pregnancy or maternity, marital or civil partner status, religion, or belief. By applying, you consent to Gravitee storing and processing the personal information you submit as part of the recruitment process.
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location This is onsite role based in Nashville, TN About the job you're considering Capgemini is hiring an Onsite Senior Software Engineer to work with a scrum team in an onshore-offshore delivery model. The ideal candidate will be responsible for developing modern, scalable, and responsive agent desktop applications using Angular and related frontend technologies while collaborating with business and technology teams to deliver high-quality solutions. Your Role • Convert Figma designs into production-ready, pixel-perfect UI components. • Build reusable component libraries and design systems for agent workflows. • Integrate UI applications with REST APIs, real-time data streams, and CCaaS platforms. • Develop responsive and accessible user interfaces across desktop environments. • Implement component-based architecture to improve scalability and maintainability. modern technology solutions and driving technical implementations. • Develop and deploy frontend applications leveraging Google Cloud Platform (GCP) services. • Work with cloud-native architectures and integrate applications with GCP-hosted APIs and services. • Work in a team covering business and technology with representatives from client to produce overall quality delivery. Your skills and experience • 3-6 years of experience in Full stack development development with strong focus on Angular applications. • Hands-on experience with Angular, TypeScript, HTML5, CSS3, and JavaScript. • Strong expertise in responsive and accessible UI design principles. • Experience integrating applications with GCP services such as Cloud Run, App Engine, Cloud Storage, Pub/Sub, and API Gateway. • Understanding of containerized deployments and CI/CD pipelines within GCP environments. • Familiarity with cloud security, monitoring, and performance optimization on GCP. • Experience developing reusable UI components and component-based architectures. • Strong understanding of frontend application design patterns and best practices. • Experience converting Figma designs into production-ready user interfaces. • Experience integrating frontend applications with REST APIs and dynamic data rendering. • Experience working with real-time data streams and CCaaS platforms is preferred. • Strong analytical thinking and problem-solving skills. • Experience performing debugging, troubleshooting, and performance optimization. • Experience working in Agile/Scrum delivery environments. • Strong communication and collaboration skills with cross-functional teams. • Ability to work independently while collaborating effectively within distributed teams. • Experience using version control tools such as Git. The base compensation range for this role in the posted location is $53,580 to $122,400 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
09/23/2026
Full time
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location This is onsite role based in Nashville, TN About the job you're considering Capgemini is hiring an Onsite Senior Software Engineer to work with a scrum team in an onshore-offshore delivery model. The ideal candidate will be responsible for developing modern, scalable, and responsive agent desktop applications using Angular and related frontend technologies while collaborating with business and technology teams to deliver high-quality solutions. Your Role • Convert Figma designs into production-ready, pixel-perfect UI components. • Build reusable component libraries and design systems for agent workflows. • Integrate UI applications with REST APIs, real-time data streams, and CCaaS platforms. • Develop responsive and accessible user interfaces across desktop environments. • Implement component-based architecture to improve scalability and maintainability. modern technology solutions and driving technical implementations. • Develop and deploy frontend applications leveraging Google Cloud Platform (GCP) services. • Work with cloud-native architectures and integrate applications with GCP-hosted APIs and services. • Work in a team covering business and technology with representatives from client to produce overall quality delivery. Your skills and experience • 3-6 years of experience in Full stack development development with strong focus on Angular applications. • Hands-on experience with Angular, TypeScript, HTML5, CSS3, and JavaScript. • Strong expertise in responsive and accessible UI design principles. • Experience integrating applications with GCP services such as Cloud Run, App Engine, Cloud Storage, Pub/Sub, and API Gateway. • Understanding of containerized deployments and CI/CD pipelines within GCP environments. • Familiarity with cloud security, monitoring, and performance optimization on GCP. • Experience developing reusable UI components and component-based architectures. • Strong understanding of frontend application design patterns and best practices. • Experience converting Figma designs into production-ready user interfaces. • Experience integrating frontend applications with REST APIs and dynamic data rendering. • Experience working with real-time data streams and CCaaS platforms is preferred. • Strong analytical thinking and problem-solving skills. • Experience performing debugging, troubleshooting, and performance optimization. • Experience working in Agile/Scrum delivery environments. • Strong communication and collaboration skills with cross-functional teams. • Ability to work independently while collaborating effectively within distributed teams. • Experience using version control tools such as Git. The base compensation range for this role in the posted location is $53,580 to $122,400 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Apple Client Platform Engineer (Remote, US) About Alectrona Customer experience is more than meeting an SLA. Our team is passionate about making Apple "just work" for our clients, because we want you to experience the delight of a truly functional technology environment, without the friction of IT getting in the way. We get excited about what we do, and we love sharing that passion with our partners. Enterprise IT becomes enjoyable again. We actually love what we do, we take a lot of pride in the quality of our work, and for us, customer experience is paramount. The SLA is not the only metric that drives us. We get deeply invested in finding ways to keep our clients as excited as we are. In an industry that hasn't changed much in over a decade, we are actively reimagining what clients should expect from technology vendors. So we want to show off what's possible not just what's been promised. We treat all people as if they're smart and know what's best. because our clients are smart, and they do know. We work with clients that inspire us, and whose missions we want to support. That mutual respect results in trusting relationships and productive communication about business pain points and solutions. We won't hide behind intimidating security-speak and IT jargon. We say what we mean, and mean for clients to understand what we say. Our clients put their people first - and so do we. Happy employees create happy customers. Downtime is expensive, and top talent shouldn't spend entire days downloading apps and setting up workstations. Our clients understand this, and demand the best for their people as a matter of business strategy. We bring a matching sense of purpose and excitement to every client engagement. What you'll do at Alectrona You will lead professional services engagements for organizations running Apple at scale. That means designing the management platform, building the parts that do not exist yet, and telling the customer the truth about what will and will not work. We're a fully remote team across multiple time zones, and we expect you to work well in that environment and be willing to meet in person a few times per year, present at conferences, and be an active member of the team. Design, deploy, and hand over Apple management platforms: MDM, identity, patching, security tooling, and the integrations that tie them together. Own services engagements end to end in accordance with our company values. You scope the work, plan it, run it, document it, and close it out. We expect you to be able to effectively manage your own time and projects. Our team enjoys this flexibility and autonomy and the responsibility that comes with it. Solve the problems that get escalated after everyone else has tried. Packet captures, log spelunking, protocol-level MDM debugging, troubleshooting undocumented behavior in macOS. Understand software development concepts: automations, integrations against vendor APIs, custom agents, deployment tooling. We don't expect you to write apps, but it is important to understand the code you're deploying and know how to fix stuff that isn't working. Challenge customers when their plan will not survive production. Arguing for a better approach is part of the job, and you have to do it well enough to keep the relationship. Run scoping calls. Uncover the business driver behind the request, and then explain what the work will take in plain language. Support our small and medium business managed services customers alongside the rest of the Alectrona team. Provide technical support and guidance to our managed services customers, including properly recording notes, updating documentation, and resolving tickets within SLA targets. Mentor other engineers and colleagues to raise the standards and help everyone learn. Shape new products and services. Alectrona builds its own software, and the ideas come from the field. Perform all job responsibilities in alignment with the core values, mission and purpose of the organization. Adhere to the highest moral, ethical and legal standards to deliver an environment that promotes respect, innovation and creativity. Support and promote a positive, inclusive workplace where the talents and strengths of our increasingly diverse workforce are welcomed, further developed, and expressed in our work. What we're looking for This is a high mid-level to senior role. We are looking for an engineer who is an expert in Apple management and knows the rest of IT well enough to work across the whole stack a customer runs. You will be supporting a variety of customer types, from end users to IT managers. Apple and endpoint management Deep experience managing Apple devices in a variety of types of environments. This means complex management beyond help desk support and basic engineering Solid hands-on expertise in at least two enterprise Apple device management platforms, and the ability to pick up the others fast. Our work spans Jamf Pro, Microsoft Intune, Omnissa Workspace ONE, Fleet, Iru (formerly Kandji), Addigy and Mosyle. Command of the Apple management stack itself, not just one vendor's console: this includes an understanding of the MDM protocol, Declarative Device Management, Automated Device Enrollment and Apple Business, APNs, configuration profiles, TCC and PPPC, FileVault, code signing and notarization, Platform SSO, etc. Experience migrating fleets between platforms, and a solid understanding of what each vendor does well and where another solution might be stronger. Software/DevOps skills for managing endpoints You are familiar with more than just using basic shell scripts. Confidence in writing your own Shell scripts and troubleshooting code at a minimum. Swift, Python, Go or other experience is a plus. Use AI to accelerate and complement your code, not as a wholesale replacement. We want efficiency, productivity, and anti-slop creativity. At Alectrona, we view AI not as a replacement for human expertise, but as a multiplier for your existing skills. Using git, participating in code review, leveraging CI, and testing and packaging are part of how you work, not something another team does for you. You leverage APIs, webhooks, and automation workflows to complete tasks and build processes that scale. The rest of IT IP networking: familiar with TCP/IP, DNS, DHCP, routing, 802.1X, VPN, proxies and TLS inspection. Server and identity administration: supporting Platform SSO, WebAuthn, Entra ID, Okta, Google Workspace, Active Directory, SAML, OIDC, SCIM, Kerberos, and certificate authorities. Security and compliance: CIS Benchmarks, NIST 800-53, SOC 2, ISO 27001, endpoint detection tooling, vulnerability management, and how each of these applies to securing Macs in production. Working with customers Experience and confidence delivering paid professional services or consulting to external customers. You are comfortable actively leading and training customers on implementing configuration changes when we aren't provided direct access to systems. Experience and confidence in supporting end users and small businesses in our managed services operation. You explain complex technical work to people who do not share your background, in writing and out loud. You participate in discovery, kickoff, and project scoping calls as the engineering voice; ask good questions and translate client context into technical decisions. You have the confidence to stand up for what's right, whether it's about a technical best practice or just common sense. You challenge your customer to think differently and maintain trust in our recommendations. You stay steady when a project goes sideways, the workload swings, or a customer is unhappy. Fluent English language proficiency (required). Education and certifications Four-year degree, or the equivalent in experience and knowledge. We understand these skills don't come from higher education alone. Appreciated, but not required; however, you should have the skill to obtain any or all of these certifications quickly: Apple Certified IT Professional, Jamf Certified Expert (400), Microsoft MD-102, CompTIA Network+ and Security+, CISSP. If you don't have certs, you will be expected to obtain them in the first few months of employment. You're the right fit for Alectrona if You enjoy your work and enjoy helping the people around you without being asked. You seek out perspectives that are not your own. You are curious and resourceful; you dig into the parts nobody else wants, and you improve on your own work. New challenges excite you rather than worry you. You take calculated risks and share your mistakes with the team so we can all improve. You approach hard conversations with empathy. Like us, you enjoy solving the really hard problems as a team and hearing how we've significantly improved our clients' working environment. We're serious about building a great place to work where we all get to enjoy what we do together. Pay and benefits The approximate annual compensation range for this role is $95,000 to $165,000, including base salary and any related bonuses or commissions. In addition, Alectrona provides benefits, including 401(k) (6% non-elective company contribution), group medical, dental, vision insurance (99% paid by Alectrona), and an unlimited vacation policy.
09/23/2026
Full time
Apple Client Platform Engineer (Remote, US) About Alectrona Customer experience is more than meeting an SLA. Our team is passionate about making Apple "just work" for our clients, because we want you to experience the delight of a truly functional technology environment, without the friction of IT getting in the way. We get excited about what we do, and we love sharing that passion with our partners. Enterprise IT becomes enjoyable again. We actually love what we do, we take a lot of pride in the quality of our work, and for us, customer experience is paramount. The SLA is not the only metric that drives us. We get deeply invested in finding ways to keep our clients as excited as we are. In an industry that hasn't changed much in over a decade, we are actively reimagining what clients should expect from technology vendors. So we want to show off what's possible not just what's been promised. We treat all people as if they're smart and know what's best. because our clients are smart, and they do know. We work with clients that inspire us, and whose missions we want to support. That mutual respect results in trusting relationships and productive communication about business pain points and solutions. We won't hide behind intimidating security-speak and IT jargon. We say what we mean, and mean for clients to understand what we say. Our clients put their people first - and so do we. Happy employees create happy customers. Downtime is expensive, and top talent shouldn't spend entire days downloading apps and setting up workstations. Our clients understand this, and demand the best for their people as a matter of business strategy. We bring a matching sense of purpose and excitement to every client engagement. What you'll do at Alectrona You will lead professional services engagements for organizations running Apple at scale. That means designing the management platform, building the parts that do not exist yet, and telling the customer the truth about what will and will not work. We're a fully remote team across multiple time zones, and we expect you to work well in that environment and be willing to meet in person a few times per year, present at conferences, and be an active member of the team. Design, deploy, and hand over Apple management platforms: MDM, identity, patching, security tooling, and the integrations that tie them together. Own services engagements end to end in accordance with our company values. You scope the work, plan it, run it, document it, and close it out. We expect you to be able to effectively manage your own time and projects. Our team enjoys this flexibility and autonomy and the responsibility that comes with it. Solve the problems that get escalated after everyone else has tried. Packet captures, log spelunking, protocol-level MDM debugging, troubleshooting undocumented behavior in macOS. Understand software development concepts: automations, integrations against vendor APIs, custom agents, deployment tooling. We don't expect you to write apps, but it is important to understand the code you're deploying and know how to fix stuff that isn't working. Challenge customers when their plan will not survive production. Arguing for a better approach is part of the job, and you have to do it well enough to keep the relationship. Run scoping calls. Uncover the business driver behind the request, and then explain what the work will take in plain language. Support our small and medium business managed services customers alongside the rest of the Alectrona team. Provide technical support and guidance to our managed services customers, including properly recording notes, updating documentation, and resolving tickets within SLA targets. Mentor other engineers and colleagues to raise the standards and help everyone learn. Shape new products and services. Alectrona builds its own software, and the ideas come from the field. Perform all job responsibilities in alignment with the core values, mission and purpose of the organization. Adhere to the highest moral, ethical and legal standards to deliver an environment that promotes respect, innovation and creativity. Support and promote a positive, inclusive workplace where the talents and strengths of our increasingly diverse workforce are welcomed, further developed, and expressed in our work. What we're looking for This is a high mid-level to senior role. We are looking for an engineer who is an expert in Apple management and knows the rest of IT well enough to work across the whole stack a customer runs. You will be supporting a variety of customer types, from end users to IT managers. Apple and endpoint management Deep experience managing Apple devices in a variety of types of environments. This means complex management beyond help desk support and basic engineering Solid hands-on expertise in at least two enterprise Apple device management platforms, and the ability to pick up the others fast. Our work spans Jamf Pro, Microsoft Intune, Omnissa Workspace ONE, Fleet, Iru (formerly Kandji), Addigy and Mosyle. Command of the Apple management stack itself, not just one vendor's console: this includes an understanding of the MDM protocol, Declarative Device Management, Automated Device Enrollment and Apple Business, APNs, configuration profiles, TCC and PPPC, FileVault, code signing and notarization, Platform SSO, etc. Experience migrating fleets between platforms, and a solid understanding of what each vendor does well and where another solution might be stronger. Software/DevOps skills for managing endpoints You are familiar with more than just using basic shell scripts. Confidence in writing your own Shell scripts and troubleshooting code at a minimum. Swift, Python, Go or other experience is a plus. Use AI to accelerate and complement your code, not as a wholesale replacement. We want efficiency, productivity, and anti-slop creativity. At Alectrona, we view AI not as a replacement for human expertise, but as a multiplier for your existing skills. Using git, participating in code review, leveraging CI, and testing and packaging are part of how you work, not something another team does for you. You leverage APIs, webhooks, and automation workflows to complete tasks and build processes that scale. The rest of IT IP networking: familiar with TCP/IP, DNS, DHCP, routing, 802.1X, VPN, proxies and TLS inspection. Server and identity administration: supporting Platform SSO, WebAuthn, Entra ID, Okta, Google Workspace, Active Directory, SAML, OIDC, SCIM, Kerberos, and certificate authorities. Security and compliance: CIS Benchmarks, NIST 800-53, SOC 2, ISO 27001, endpoint detection tooling, vulnerability management, and how each of these applies to securing Macs in production. Working with customers Experience and confidence delivering paid professional services or consulting to external customers. You are comfortable actively leading and training customers on implementing configuration changes when we aren't provided direct access to systems. Experience and confidence in supporting end users and small businesses in our managed services operation. You explain complex technical work to people who do not share your background, in writing and out loud. You participate in discovery, kickoff, and project scoping calls as the engineering voice; ask good questions and translate client context into technical decisions. You have the confidence to stand up for what's right, whether it's about a technical best practice or just common sense. You challenge your customer to think differently and maintain trust in our recommendations. You stay steady when a project goes sideways, the workload swings, or a customer is unhappy. Fluent English language proficiency (required). Education and certifications Four-year degree, or the equivalent in experience and knowledge. We understand these skills don't come from higher education alone. Appreciated, but not required; however, you should have the skill to obtain any or all of these certifications quickly: Apple Certified IT Professional, Jamf Certified Expert (400), Microsoft MD-102, CompTIA Network+ and Security+, CISSP. If you don't have certs, you will be expected to obtain them in the first few months of employment. You're the right fit for Alectrona if You enjoy your work and enjoy helping the people around you without being asked. You seek out perspectives that are not your own. You are curious and resourceful; you dig into the parts nobody else wants, and you improve on your own work. New challenges excite you rather than worry you. You take calculated risks and share your mistakes with the team so we can all improve. You approach hard conversations with empathy. Like us, you enjoy solving the really hard problems as a team and hearing how we've significantly improved our clients' working environment. We're serious about building a great place to work where we all get to enjoy what we do together. Pay and benefits The approximate annual compensation range for this role is $95,000 to $165,000, including base salary and any related bonuses or commissions. In addition, Alectrona provides benefits, including 401(k) (6% non-elective company contribution), group medical, dental, vision insurance (99% paid by Alectrona), and an unlimited vacation policy.
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next-generation RISC-V and AI compute architectures. You will work across hardware and software teams to improve performance, programmability, and integration of our custom toolchains into real applications. This role is fully hands-on and central to how developers interact with Tenstorrent hardware across both traditional compute and advanced machine learning workloads. This role isHybrid, based out of Santa Clara, CA, Austin, TX, or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced compiler engineer with deep knowledge of GCC and LLVM internals, comfortable optimizing for custom hardware targets. Strong C/C++ developer with a solid grasp of algorithms, data structures, and performance analysis. Collaborative and analytical, able to work across hardware and software domains to deliver efficient, high-performance toolchains. Passionate about enabling breakthrough compute architectures through compiler innovation and software-hardware co-design. What We Need Design, develop, and optimize GCC and/or LLVM compilers for Tenstorrent's custom RISC-V hardware and AI vector engines. Contribute to the co-design of Tenstorrent's hardware and software stack to maximize performance and programmability. Benchmark, analyze, and tune performance of core applications across RISC-V and AI software environments. Collaborate with ML engineers to identify and implement compiler support for emerging AI workloads and frameworks. What You'll Learn How compiler design directly impacts the performance and efficiency of next-generation RISC-V and AI architectures. Advanced techniques in hardware-software co-optimization and compiler-driven performance tuning. Integration of custom compilers with leading ML frameworks and runtime environments. The end-to-end toolchain flow that enables Tenstorrent's scalable, high-performance AI compute systems. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next-generation RISC-V and AI compute architectures. You will work across hardware and software teams to improve performance, programmability, and integration of our custom toolchains into real applications. This role is fully hands-on and central to how developers interact with Tenstorrent hardware across both traditional compute and advanced machine learning workloads. This role isHybrid, based out of Santa Clara, CA, Austin, TX, or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced compiler engineer with deep knowledge of GCC and LLVM internals, comfortable optimizing for custom hardware targets. Strong C/C++ developer with a solid grasp of algorithms, data structures, and performance analysis. Collaborative and analytical, able to work across hardware and software domains to deliver efficient, high-performance toolchains. Passionate about enabling breakthrough compute architectures through compiler innovation and software-hardware co-design. What We Need Design, develop, and optimize GCC and/or LLVM compilers for Tenstorrent's custom RISC-V hardware and AI vector engines. Contribute to the co-design of Tenstorrent's hardware and software stack to maximize performance and programmability. Benchmark, analyze, and tune performance of core applications across RISC-V and AI software environments. Collaborate with ML engineers to identify and implement compiler support for emerging AI workloads and frameworks. What You'll Learn How compiler design directly impacts the performance and efficiency of next-generation RISC-V and AI architectures. Advanced techniques in hardware-software co-optimization and compiler-driven performance tuning. Integration of custom compilers with leading ML frameworks and runtime environments. The end-to-end toolchain flow that enables Tenstorrent's scalable, high-performance AI compute systems. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Job Description About us New Co is a new AI-native product organization within Capgemini Financial Services. We build products, not projects: software for insurance claims, payment operations, and health operations, sold to banks, insurers, and health plans. Three product lines run on one shared platform, built by a deliberately small, senior team. Our engineering model is agentic: engineers author the specifications, tooling, evaluation suites, and guardrails, and AI agents do most of the implementation. Humans own every consequential decision, and in our regulated domains some decisions are human-only by design. The role Three product lines, one platform. You will own the platform that Claims, Payments, and Health run on: the agentic AI floor (model gateway, agent runtime, evaluation infrastructure, guardrails) and the shared product services around it (case management and work queues, integration connectors, multi-tenancy, metering). You run the platform as a product whose customers are our product teams, and you are its first and most senior engineer-leader. Every hour of claims handling or payment processing our products automate rests on infrastructure your group builds. What you will own The strategic vision, roadmap, and end-to-end lifecycle of the platform: from the model gateway and agent runtime to shared workflow, tenancy, and metering services A competitive engineering strategy at the frontier: you track research and model releases as they land, decide what the platform adopts versus builds, and keep our capability curve ahead of what clients could assemble themselves The closed improvement loops: production signals and evaluation verdicts feed reinforcement learning and fine-tuning pipelines that produce our own LLMs and SLMs; product loops run automated end to end, with humans holding the gates Build-vs-buy decisions across open-source and commercial AI infrastructure, and the boundary between what the platform provides and what product lines build themselves A disciplined operating model: a published capacity split between product-team requests, platform quality, and strategic initiatives; services graduate to self-service only when they are ready Platform adoption outcomes: your group is measured by the delivery metrics of its consumers, not its own output Compliance posture of the platform in regulated environments: model risk documentation, audit trails, and responsible-AI practices that bank and insurer risk teams can examine; no AI capability ships ungoverned or unevaluated, including the models we train ourselves Hiring and growing the platform group, and the engineering standards it sets for the whole organization What you will need A track record leading platform or infrastructure teams that ran production systems for multiple product teams, with accountability for adoption, not just delivery Hands-on credibility in modern AI infrastructure: LLM inference and serving, model gateways, vector search, guardrails, and evaluation systems Frontier research fluency: you read post-training, reinforcement learning, and agentic-systems work as it lands and can turn it into engineering strategy; an engineer who reads research, not a researcher at engineering distance Cloud platform depth (AWS, Azure, or GCP) with Kubernetes and infrastructure-as-code at production scale Experience delivering in a regulated industry, ideally financial services, or demonstrable fluency in what model-risk and security review requires of a platform A platform-as-product mindset: you can talk about golden paths, voluntary adoption, and developer research as naturally as architecture Daily, hands-on use of AI coding assistants in your own work What sets you apart You have owned both an AI platform floor and shared business services (workflow, tenancy, billing/metering) in one charter You have taken a model through post-training (RLHF, RLAIF, fine-tuning, or distillation to smaller models) into production Published or open-source work in agent infrastructure or evaluation tooling Cost management (FinOps) experience for LLM workloads Financial services domain depth: you have shipped production systems for banks, insurers, or payment providers The reference stack The reference technology stack for this role is our supported paved road: self-hosted Lang Smith and Lang Graph Platform as the agent runtime and evaluation plane, model providers behind a swappable gateway seam, PostgreSQL with pg vector plus Click House and S3-compatible object storage as the data platform, Neo4j Enterprise as the semantic knowledge graph, an agent memory plane serving episodic and precedent memory over MCP, MCP-native connectors, Open Telemetry and Grafana for observability, all on CNCF-conformant Kubernetes with Helm and Argo CD, deployable to any hyper scaler or on-prem. A tool-for-tool match is not expected: analogous experience counts fully. If you have built and operated systems of this shape on comparable components (a different orchestration framework, graph engine, evaluation platform, or serving stack), you have what we are looking for. How we work Engineers write specs, harnesses, evals, and guardrails; AI agents execute the implementation loops. Review, not typing, is where engineering judgment goes. Three human gates govern everything we ship: spec approval, merge, and release. Regulated code paths (money movement, authentication, cryptography, secrets) are always human-owned. Small and senior by design. No separate QA function, no scrum masters; quality comes from evaluation gates and whole-team review rituals. Domain experts (claims practitioners, payment scheme experts, clinicians) are full-time members of the product teams you will serve. Success in year one The first product line ships to its first enterprise client on platform services it chose to use, with platform cost attributed per line Platform adoption is voluntary and measured; product teams' deployment frequency and change-failure rates improve after adoption Bank or insurer model-risk teams accept the platform's evidence pack on first review A written engineering strategy exists, is re-argued each quarter against frontier developments, and the first New Co-tuned model (LLM or SLM) serves production traffic behind evaluation gates The base compensation range for this role in the posted location is 141546 - 203155 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment . click apply for full job details
09/23/2026
Full time
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Job Description About us New Co is a new AI-native product organization within Capgemini Financial Services. We build products, not projects: software for insurance claims, payment operations, and health operations, sold to banks, insurers, and health plans. Three product lines run on one shared platform, built by a deliberately small, senior team. Our engineering model is agentic: engineers author the specifications, tooling, evaluation suites, and guardrails, and AI agents do most of the implementation. Humans own every consequential decision, and in our regulated domains some decisions are human-only by design. The role Three product lines, one platform. You will own the platform that Claims, Payments, and Health run on: the agentic AI floor (model gateway, agent runtime, evaluation infrastructure, guardrails) and the shared product services around it (case management and work queues, integration connectors, multi-tenancy, metering). You run the platform as a product whose customers are our product teams, and you are its first and most senior engineer-leader. Every hour of claims handling or payment processing our products automate rests on infrastructure your group builds. What you will own The strategic vision, roadmap, and end-to-end lifecycle of the platform: from the model gateway and agent runtime to shared workflow, tenancy, and metering services A competitive engineering strategy at the frontier: you track research and model releases as they land, decide what the platform adopts versus builds, and keep our capability curve ahead of what clients could assemble themselves The closed improvement loops: production signals and evaluation verdicts feed reinforcement learning and fine-tuning pipelines that produce our own LLMs and SLMs; product loops run automated end to end, with humans holding the gates Build-vs-buy decisions across open-source and commercial AI infrastructure, and the boundary between what the platform provides and what product lines build themselves A disciplined operating model: a published capacity split between product-team requests, platform quality, and strategic initiatives; services graduate to self-service only when they are ready Platform adoption outcomes: your group is measured by the delivery metrics of its consumers, not its own output Compliance posture of the platform in regulated environments: model risk documentation, audit trails, and responsible-AI practices that bank and insurer risk teams can examine; no AI capability ships ungoverned or unevaluated, including the models we train ourselves Hiring and growing the platform group, and the engineering standards it sets for the whole organization What you will need A track record leading platform or infrastructure teams that ran production systems for multiple product teams, with accountability for adoption, not just delivery Hands-on credibility in modern AI infrastructure: LLM inference and serving, model gateways, vector search, guardrails, and evaluation systems Frontier research fluency: you read post-training, reinforcement learning, and agentic-systems work as it lands and can turn it into engineering strategy; an engineer who reads research, not a researcher at engineering distance Cloud platform depth (AWS, Azure, or GCP) with Kubernetes and infrastructure-as-code at production scale Experience delivering in a regulated industry, ideally financial services, or demonstrable fluency in what model-risk and security review requires of a platform A platform-as-product mindset: you can talk about golden paths, voluntary adoption, and developer research as naturally as architecture Daily, hands-on use of AI coding assistants in your own work What sets you apart You have owned both an AI platform floor and shared business services (workflow, tenancy, billing/metering) in one charter You have taken a model through post-training (RLHF, RLAIF, fine-tuning, or distillation to smaller models) into production Published or open-source work in agent infrastructure or evaluation tooling Cost management (FinOps) experience for LLM workloads Financial services domain depth: you have shipped production systems for banks, insurers, or payment providers The reference stack The reference technology stack for this role is our supported paved road: self-hosted Lang Smith and Lang Graph Platform as the agent runtime and evaluation plane, model providers behind a swappable gateway seam, PostgreSQL with pg vector plus Click House and S3-compatible object storage as the data platform, Neo4j Enterprise as the semantic knowledge graph, an agent memory plane serving episodic and precedent memory over MCP, MCP-native connectors, Open Telemetry and Grafana for observability, all on CNCF-conformant Kubernetes with Helm and Argo CD, deployable to any hyper scaler or on-prem. A tool-for-tool match is not expected: analogous experience counts fully. If you have built and operated systems of this shape on comparable components (a different orchestration framework, graph engine, evaluation platform, or serving stack), you have what we are looking for. How we work Engineers write specs, harnesses, evals, and guardrails; AI agents execute the implementation loops. Review, not typing, is where engineering judgment goes. Three human gates govern everything we ship: spec approval, merge, and release. Regulated code paths (money movement, authentication, cryptography, secrets) are always human-owned. Small and senior by design. No separate QA function, no scrum masters; quality comes from evaluation gates and whole-team review rituals. Domain experts (claims practitioners, payment scheme experts, clinicians) are full-time members of the product teams you will serve. Success in year one The first product line ships to its first enterprise client on platform services it chose to use, with platform cost attributed per line Platform adoption is voluntary and measured; product teams' deployment frequency and change-failure rates improve after adoption Bank or insurer model-risk teams accept the platform's evidence pack on first review A written engineering strategy exists, is re-argued each quarter against frontier developments, and the first New Co-tuned model (LLM or SLM) serves production traffic behind evaluation gates The base compensation range for this role in the posted location is 141546 - 203155 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment . click apply for full job details
About Us Stic is modernizing out-of-home, one of advertising's oldest formats. Billboards and transit ads have always sold impressions on faith. Stic replaces faith by turning everyday vehicles into GPS-tracked, mobile media. Brands get proof instead of best guesses. Drivers earn passive income on miles they're already driving. Stic Vision is how it works. An edge AI device small enough to live inside a decal, streaming informative analytics with no vehicle-level integration required. The global out-of-home advertising market is worth roughly $40 billion a year. Stic is building the measurement layer that legacy OOH never had. Stic is trusted by brands like TikTok, Dunkin Donuts, e.l.f., and PacSun. The traction is already showing up in results: a SXSW campaign for TikTok Radio put 44 vehicles on the road in Austin and generated 3.9 million tracked impressions. That's real, revenue-generating proof in a category still mostly sold on assumptions. Stic is lean by design. People joining now build the playbook rather than inheriting one. This means fast execution, without the layers of process that slow down bigger companies. About You As a Senior Embedded Software Engineer at Stic, you will own the firmware and low-level software stack for the Stic Vision v3.0. A sticker-form-factor edge AI device that deploys on any vehicle, any window, any surface, delivering machine vision, real-time analytics, and AI inference at the edge without any vehicle-level integration. This role sits at the intersection of hardware and intelligence: you will write the firmware that drives computer vision, wireless communication, and sensor fusion on a compact, low-power device operating in real-world automotive environments. Stic's mission is to bring edge AI sensing to the 1.4 billion legacy vehicles that autonomous platforms cannot reach. This role is foundational to that mission. The firmware you write is what turns a manufacturable sticker into a living sensor node. Why This Role Matters This role is the backbone of Stic's transition from prototype to a fully integrated, proprietary hardware and intelligence platform. The firmware you write directly powers data capture, edge intelligence, and real-world deployment at scale across the largest untapped sensor network on the planet: the existing vehicle fleet. What You'll Do Develop and maintain embedded firmware in C/C++ for microcontrollers and wireless modules powering the Stic Vision v3.0 Own OpenMV-based computer vision firmware for person detection, vehicle counting, facial sentiment analysis, and demographic measurement Implement BLE communication stacks - advertising, scanning, data payloads, and RSSI-based logic Integrate cellular (LTE/5G), GNSS, IMU, camera, and sensor interfaces into a unified firmware architecture Build low-power firmware architectures including sleep states, duty cycling, and battery optimization for field-deployed devices Define and implement device-to-cloud and device-to-phone communication protocols Support OTA update pipelines, field diagnostics, and reliability improvements Collaborate with hardware, computer vision, and cloud teams to ensure seamless full-stack integration Contribute to board bring-up, hardware/firmware debugging, and system validation across EVT/DVT/PVT cycles What You Have to Have 3-5+ years of professional embedded software engineering experience Strong proficiency in C, micropython and C++ for embedded systems Hands-on experience with BLE firmware development (advertising, scanning, payload design, RSSI logic) Experience with real-time operating systems (RTOS), interrupt handling, and low-level memory management Familiarity with communication protocols including SPI, I2C, UART, and wireless stacks Proficiency with debugging tools including JTAG, oscilloscopes, and logic analyzers Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience What You Should Ideally Have Experience with OpenMV or similar embedded computer vision / ML-enabled camera modules Familiarity with nRF, STM32, Snapdragon, NVIDIA Jetson, ESP32, or similar platforms Experience with LTE/5G module integration and GNSS systems Background in edge AI inference, sensor fusion, or on-device ML Exposure to EVT/DVT/PVT processes and scaling hardware from prototype to production Experience in IoT, automotive, or rugged field-deployed systems Base Salary: $130,000 - $190,000 Work Location: Los Angeles - in person Benefits Join a well-funded early-stage company disrupting traditional advertising with patent pending technology 26 days off per year (15 PTO / 11 holidays) prorated for any partial year of employment Explosive career growth Health & dental insurance 401(k) Equal Employment Opportunity Stic is an equal opportunity employer committed to building a diverse, equitable, and inclusive workplace. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, ancestry, citizenship, disability, genetic information, medical condition, marital status, military or veteran status, or any other characteristic protected by federal, state, or local law. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Use of Artificial Intelligence and Automated Tools in Recruiting Stic uses artificial intelligence and automated tools in parts of our recruiting process. These tools may help organize and review applications, transcribe or summarize interviews, and assist our team in assessing job-related qualifications. Artificial intelligence does not make hiring decisions. A member of our team reviews candidate materials and makes every screening, interview, and hiring decision. We do not use these tools to evaluate candidates on the basis of race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, religion, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by federal or California law. Reasonable Accommodations & Alternative Process Stic is committed to providing reasonable accommodations for qualified individuals with disabilities and individuals with sincerely held religious beliefs in our job application and interview procedures. If you need assistance or an accommodation due to a disability, wish to request an alternative to any AI-assisted step in our recruiting process, or have questions about how these tools are used, please contact us at . Requesting an accommodation or alternative will not negatively impact your application or candidacy. Privacy Notice at Collection Personal information we collect includes identifiers, biometric information, internet activity, geolocation data, audio, electronic, video, or image information, professional or employment-related information, and inferences drawn from the above information. We do not sell your personal information. We may share your personal information with service providers who assist with payment processing, data analytics, campaign management, and technology infrastructure, and with brand partners to the extent necessary to demonstrate campaign performance. We do not share your personal information for cross-context behavioral advertising.
09/23/2026
Full time
About Us Stic is modernizing out-of-home, one of advertising's oldest formats. Billboards and transit ads have always sold impressions on faith. Stic replaces faith by turning everyday vehicles into GPS-tracked, mobile media. Brands get proof instead of best guesses. Drivers earn passive income on miles they're already driving. Stic Vision is how it works. An edge AI device small enough to live inside a decal, streaming informative analytics with no vehicle-level integration required. The global out-of-home advertising market is worth roughly $40 billion a year. Stic is building the measurement layer that legacy OOH never had. Stic is trusted by brands like TikTok, Dunkin Donuts, e.l.f., and PacSun. The traction is already showing up in results: a SXSW campaign for TikTok Radio put 44 vehicles on the road in Austin and generated 3.9 million tracked impressions. That's real, revenue-generating proof in a category still mostly sold on assumptions. Stic is lean by design. People joining now build the playbook rather than inheriting one. This means fast execution, without the layers of process that slow down bigger companies. About You As a Senior Embedded Software Engineer at Stic, you will own the firmware and low-level software stack for the Stic Vision v3.0. A sticker-form-factor edge AI device that deploys on any vehicle, any window, any surface, delivering machine vision, real-time analytics, and AI inference at the edge without any vehicle-level integration. This role sits at the intersection of hardware and intelligence: you will write the firmware that drives computer vision, wireless communication, and sensor fusion on a compact, low-power device operating in real-world automotive environments. Stic's mission is to bring edge AI sensing to the 1.4 billion legacy vehicles that autonomous platforms cannot reach. This role is foundational to that mission. The firmware you write is what turns a manufacturable sticker into a living sensor node. Why This Role Matters This role is the backbone of Stic's transition from prototype to a fully integrated, proprietary hardware and intelligence platform. The firmware you write directly powers data capture, edge intelligence, and real-world deployment at scale across the largest untapped sensor network on the planet: the existing vehicle fleet. What You'll Do Develop and maintain embedded firmware in C/C++ for microcontrollers and wireless modules powering the Stic Vision v3.0 Own OpenMV-based computer vision firmware for person detection, vehicle counting, facial sentiment analysis, and demographic measurement Implement BLE communication stacks - advertising, scanning, data payloads, and RSSI-based logic Integrate cellular (LTE/5G), GNSS, IMU, camera, and sensor interfaces into a unified firmware architecture Build low-power firmware architectures including sleep states, duty cycling, and battery optimization for field-deployed devices Define and implement device-to-cloud and device-to-phone communication protocols Support OTA update pipelines, field diagnostics, and reliability improvements Collaborate with hardware, computer vision, and cloud teams to ensure seamless full-stack integration Contribute to board bring-up, hardware/firmware debugging, and system validation across EVT/DVT/PVT cycles What You Have to Have 3-5+ years of professional embedded software engineering experience Strong proficiency in C, micropython and C++ for embedded systems Hands-on experience with BLE firmware development (advertising, scanning, payload design, RSSI logic) Experience with real-time operating systems (RTOS), interrupt handling, and low-level memory management Familiarity with communication protocols including SPI, I2C, UART, and wireless stacks Proficiency with debugging tools including JTAG, oscilloscopes, and logic analyzers Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience What You Should Ideally Have Experience with OpenMV or similar embedded computer vision / ML-enabled camera modules Familiarity with nRF, STM32, Snapdragon, NVIDIA Jetson, ESP32, or similar platforms Experience with LTE/5G module integration and GNSS systems Background in edge AI inference, sensor fusion, or on-device ML Exposure to EVT/DVT/PVT processes and scaling hardware from prototype to production Experience in IoT, automotive, or rugged field-deployed systems Base Salary: $130,000 - $190,000 Work Location: Los Angeles - in person Benefits Join a well-funded early-stage company disrupting traditional advertising with patent pending technology 26 days off per year (15 PTO / 11 holidays) prorated for any partial year of employment Explosive career growth Health & dental insurance 401(k) Equal Employment Opportunity Stic is an equal opportunity employer committed to building a diverse, equitable, and inclusive workplace. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, ancestry, citizenship, disability, genetic information, medical condition, marital status, military or veteran status, or any other characteristic protected by federal, state, or local law. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Use of Artificial Intelligence and Automated Tools in Recruiting Stic uses artificial intelligence and automated tools in parts of our recruiting process. These tools may help organize and review applications, transcribe or summarize interviews, and assist our team in assessing job-related qualifications. Artificial intelligence does not make hiring decisions. A member of our team reviews candidate materials and makes every screening, interview, and hiring decision. We do not use these tools to evaluate candidates on the basis of race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, religion, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by federal or California law. Reasonable Accommodations & Alternative Process Stic is committed to providing reasonable accommodations for qualified individuals with disabilities and individuals with sincerely held religious beliefs in our job application and interview procedures. If you need assistance or an accommodation due to a disability, wish to request an alternative to any AI-assisted step in our recruiting process, or have questions about how these tools are used, please contact us at . Requesting an accommodation or alternative will not negatively impact your application or candidacy. Privacy Notice at Collection Personal information we collect includes identifiers, biometric information, internet activity, geolocation data, audio, electronic, video, or image information, professional or employment-related information, and inferences drawn from the above information. We do not sell your personal information. We may share your personal information with service providers who assist with payment processing, data analytics, campaign management, and technology infrastructure, and with brand partners to the extent necessary to demonstrate campaign performance. We do not share your personal information for cross-context behavioral advertising.
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly technical Senior Staff/Principal Engineer to lead the porting and enablement of critical AI workloads. You will be a primary driver in migrating compute workloads to RISC-V architectures, ensuring our hardware is optimized for real-world application performance. The ideal candidate has a strong background in DevOps, workload porting, or application enablement . While this is an individual contributor role at its core, you will have the opportunity to grow and lead a small, specialized team over time as our workload migration efforts scale. This role is remote, based in the United States or Australia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A Technical Catalyst: You thrive on the challenge of driving AI hardware porting to RISC-V and making complex software stacks run efficiently on new hardware. Systems Expert: You possess deep knowledge of system software, compilers, or low-level OS internals. You are an expert in ARM or x86 environments and are ready to apply those skills to the RISC-V frontier. A Project Driver: You have the technical authority to lead the implementation of a compute migration to RISC-V through strategic IT and DevOps enablement. Collaborative & Cross-Functional: You enjoy acting as the "technical glue" between IT, DevOps, and AI teams , coordinating complex efforts across boundaries to ensure seamless workload transitions. Architecture Agnostic: You are a systems thinker who understands how to bridge the gap between infrastructure and core silicon engineering. What We Need Education: BS/MS/PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Workload Expertise: Extensive experience in workload porting, DevOps engineering, or application enablement . Systems Fluency: Strong familiarity with CPU architectures and systems design, with a proven track record of troubleshooting and optimizing performance across new architectures. Leadership Qualities: Ability to coordinate across multiple technical teams and the potential to mentor or grow a small engineering pod. Execution Focus: A mindset geared toward technical delivery and methodology development rather than broad community networking. What You Will Learn Gain deep expertise in bleeding-edge RISC-V system software across server and AI-accelerated environments. Directly influence an upcoming project , a high-visibility initiative shaping the future of our internal compute infrastructure. Work at the intersection of AI/ML workloads and hardware/software co-design. Shape the technical roadmap for how the industry adopts RISC-V for high-performance compute. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly technical Senior Staff/Principal Engineer to lead the porting and enablement of critical AI workloads. You will be a primary driver in migrating compute workloads to RISC-V architectures, ensuring our hardware is optimized for real-world application performance. The ideal candidate has a strong background in DevOps, workload porting, or application enablement . While this is an individual contributor role at its core, you will have the opportunity to grow and lead a small, specialized team over time as our workload migration efforts scale. This role is remote, based in the United States or Australia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A Technical Catalyst: You thrive on the challenge of driving AI hardware porting to RISC-V and making complex software stacks run efficiently on new hardware. Systems Expert: You possess deep knowledge of system software, compilers, or low-level OS internals. You are an expert in ARM or x86 environments and are ready to apply those skills to the RISC-V frontier. A Project Driver: You have the technical authority to lead the implementation of a compute migration to RISC-V through strategic IT and DevOps enablement. Collaborative & Cross-Functional: You enjoy acting as the "technical glue" between IT, DevOps, and AI teams , coordinating complex efforts across boundaries to ensure seamless workload transitions. Architecture Agnostic: You are a systems thinker who understands how to bridge the gap between infrastructure and core silicon engineering. What We Need Education: BS/MS/PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Workload Expertise: Extensive experience in workload porting, DevOps engineering, or application enablement . Systems Fluency: Strong familiarity with CPU architectures and systems design, with a proven track record of troubleshooting and optimizing performance across new architectures. Leadership Qualities: Ability to coordinate across multiple technical teams and the potential to mentor or grow a small engineering pod. Execution Focus: A mindset geared toward technical delivery and methodology development rather than broad community networking. What You Will Learn Gain deep expertise in bleeding-edge RISC-V system software across server and AI-accelerated environments. Directly influence an upcoming project , a high-visibility initiative shaping the future of our internal compute infrastructure. Work at the intersection of AI/ML workloads and hardware/software co-design. Shape the technical roadmap for how the industry adopts RISC-V for high-performance compute. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Onboard Software Performance team ensures that systems running on ADV (Autonomously Driven Vehicle) meet strict performance requirements such as producing necessary outputs within strict latency targets and using an appropriately allocated amount of compute resources (CPU/GPU/TPU/RAM etc) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while enabling high velocity of system evolution. In this hybrid role, you will report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's modular architecture improvements and frameworks that maximize performance and compute utilization and ROI for driving quality Evolve our compute usage on the car and simulation to enable continued scaling where the system runs fast on the car and efficiently in our data center Collaborating with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality Collaborating with hardware teams to codesign hardware/software and optimize the software for best performance on our hardware platform Ensuring our performance is strong at any driving complexity including as we scale to even more complex driving environments and encounter rarer events Ensuring state of the art reaction latency for collision avoidance via novel system/architecture designs and extremely fast nominal performance Developing necessary high scale performance evaluation, debugging and software change management processes Optimizing system resource usage to simulation at scale in Cloud datacenters: minimizing CPU utilization and latency, minimizing RAM consumption, intelligently determining which computations should happen on CPU, GPU, and TPU. You have: BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience) 6 years of software engineering experience on large scale/high complexity system (supported by hundreds of engineers) 2 years of software management experience with at least 4 years in infrastructure/systems/performance domain optimizing end to end system for high performance metrics 4 years of experience acting as technical lead in performance/software infrastructure domain 4 years of experience in C++ Define roadmap/portfolio of projects optimizing for end results overall across all aspects of the problem space Setup collaboration structures across team boundaries We prefer: Experience in robotics Experience in low level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience in large scale evaluation techniques/data science and building performance metrics/tooling Experience in large scale software re-architecture projects The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Onboard Software Performance team ensures that systems running on ADV (Autonomously Driven Vehicle) meet strict performance requirements such as producing necessary outputs within strict latency targets and using an appropriately allocated amount of compute resources (CPU/GPU/TPU/RAM etc) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while enabling high velocity of system evolution. In this hybrid role, you will report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's modular architecture improvements and frameworks that maximize performance and compute utilization and ROI for driving quality Evolve our compute usage on the car and simulation to enable continued scaling where the system runs fast on the car and efficiently in our data center Collaborating with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality Collaborating with hardware teams to codesign hardware/software and optimize the software for best performance on our hardware platform Ensuring our performance is strong at any driving complexity including as we scale to even more complex driving environments and encounter rarer events Ensuring state of the art reaction latency for collision avoidance via novel system/architecture designs and extremely fast nominal performance Developing necessary high scale performance evaluation, debugging and software change management processes Optimizing system resource usage to simulation at scale in Cloud datacenters: minimizing CPU utilization and latency, minimizing RAM consumption, intelligently determining which computations should happen on CPU, GPU, and TPU. You have: BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience) 6 years of software engineering experience on large scale/high complexity system (supported by hundreds of engineers) 2 years of software management experience with at least 4 years in infrastructure/systems/performance domain optimizing end to end system for high performance metrics 4 years of experience acting as technical lead in performance/software infrastructure domain 4 years of experience in C++ Define roadmap/portfolio of projects optimizing for end results overall across all aspects of the problem space Setup collaboration structures across team boundaries We prefer: Experience in robotics Experience in low level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience in large scale evaluation techniques/data science and building performance metrics/tooling Experience in large scale software re-architecture projects The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's commercial service is running in five cities, and the associated infrastructure is in an early stage and requires investment for Waymo to grow into a high scale, world-class service. We are building a team of engineers dedicated to further developing our Android Platform team. Our team works on the user interfaces used by customers to interact with our autonomous vehicles as well as provide entertainment and information while riding. This is a fullstack team, managing the bring up and maintenance of a complete automotive grade Android system. In this hybrid role, you will report to an Engineering Manager. You will: Evaluate SoC vendor development kits Develop update mechanism for Android OS and applications Work with vendors, HW team and other stakeholders to define requirements for next UX platform Bring up Android on new hardware Provide technical support for other teams working on our Android devices You have: BS/MS degree in Computer Science or equivalent experience 3+ years of software development experience Experience working with low-level Android/AOSP (building Android platform features, frameworks), not just developing apps on top of Android Worked with git, repo and gerrit We prefer: Brought up Android on new hardware, or customized a build of Android for a new hardware variant Experience with security aspects of Android, SELinux and key provisioning The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $170,000-$216,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's commercial service is running in five cities, and the associated infrastructure is in an early stage and requires investment for Waymo to grow into a high scale, world-class service. We are building a team of engineers dedicated to further developing our Android Platform team. Our team works on the user interfaces used by customers to interact with our autonomous vehicles as well as provide entertainment and information while riding. This is a fullstack team, managing the bring up and maintenance of a complete automotive grade Android system. In this hybrid role, you will report to an Engineering Manager. You will: Evaluate SoC vendor development kits Develop update mechanism for Android OS and applications Work with vendors, HW team and other stakeholders to define requirements for next UX platform Bring up Android on new hardware Provide technical support for other teams working on our Android devices You have: BS/MS degree in Computer Science or equivalent experience 3+ years of software development experience Experience working with low-level Android/AOSP (building Android platform features, frameworks), not just developing apps on top of Android Worked with git, repo and gerrit We prefer: Brought up Android on new hardware, or customized a build of Android for a new hardware variant Experience with security aspects of Android, SELinux and key provisioning The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $170,000-$216,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo Driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques. These techniques are for the Evaluation systems on our autonomous service. They will serve as a constant driver to improve the performance of our technology stack. You will: Grow the end-to-end strategy for our next generation of machine learning-based evaluation metrics, promoting scientific and statistical rigor across our embodied AI applications Architect and build scalable systems for training and fine-tuning large-scale generative models to produce realistic and evaluate interesting driving behaviors Lead the design, implementation, and iteration of novel RL algorithms, reward functions, and training paradigms tailored for generating high-fidelity and insightful driving behaviors Lead the development of cutting-edge Deep Learning models and Generative AI (LLM/VLM) solutions. These solutions will enhance human-led triaging, introduce automation for high-volume workflows, and perform nuanced analysis of self-driving behavior to detect critical anomalies Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system Provide technical mentorship, guidance, and thought leadership to other engineers within the team and across collaborating groups Guide and align multiple teams-including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software-on a cohesive evaluation strategy, ensuring cross-functional alignment on goals and priorities You have: PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience 10+ years of hands-on experience in developing and applying Machine Learning models, with a significant focus on Reinforcement Learning 2+ years of people management experience Demonstrated expertise in deep learning, sequence modeling, and generative models Strong publication record or history of impactful project delivery in RL or related areas Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow) Experience with large-scale distributed training and data processing Proven ability to lead complex and ambiguous technical projects from conception to completion We prefer: 12+ years of relevant experience in ML/RL research and application Experience in the autonomous vehicles domain, robotics, or complex simulation environments Deep understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences) Familiarity with large-scale simulation platforms and their integration with ML training workflows Experience designing and using metrics for evaluating complex AI systems Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries Excellent communication skills, with the ability to articulate complex technical concepts clearly The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo Driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques. These techniques are for the Evaluation systems on our autonomous service. They will serve as a constant driver to improve the performance of our technology stack. You will: Grow the end-to-end strategy for our next generation of machine learning-based evaluation metrics, promoting scientific and statistical rigor across our embodied AI applications Architect and build scalable systems for training and fine-tuning large-scale generative models to produce realistic and evaluate interesting driving behaviors Lead the design, implementation, and iteration of novel RL algorithms, reward functions, and training paradigms tailored for generating high-fidelity and insightful driving behaviors Lead the development of cutting-edge Deep Learning models and Generative AI (LLM/VLM) solutions. These solutions will enhance human-led triaging, introduce automation for high-volume workflows, and perform nuanced analysis of self-driving behavior to detect critical anomalies Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system Provide technical mentorship, guidance, and thought leadership to other engineers within the team and across collaborating groups Guide and align multiple teams-including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software-on a cohesive evaluation strategy, ensuring cross-functional alignment on goals and priorities You have: PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience 10+ years of hands-on experience in developing and applying Machine Learning models, with a significant focus on Reinforcement Learning 2+ years of people management experience Demonstrated expertise in deep learning, sequence modeling, and generative models Strong publication record or history of impactful project delivery in RL or related areas Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow) Experience with large-scale distributed training and data processing Proven ability to lead complex and ambiguous technical projects from conception to completion We prefer: 12+ years of relevant experience in ML/RL research and application Experience in the autonomous vehicles domain, robotics, or complex simulation environments Deep understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences) Familiarity with large-scale simulation platforms and their integration with ML training workflows Experience designing and using metrics for evaluating complex AI systems Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries Excellent communication skills, with the ability to articulate complex technical concepts clearly The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's commercial service is up and running in multiple cities, with ambitious plans to expand dramatically in the coming years; the associated infrastructure is in an early stage and requires significant investment for Waymo to grow into a high scale, world-class service. Increasing demand for Waymo's ride-hailing service will drive evolution of our systems, providing an opportunity-rich environment to solve hard, ambiguous, high-impact, cross-functional problems. Team: Fleet Management Project: Workshop management; focused on planning and executing vehicle maintenance and uptime software. In this hybrid role, you will report to an Engineering Manager. You will: Design, develop, test, and optimize Angular applications using Typescript and modern development techniques. Build and evolve mission-critical tools and systems that allow Waymo to scale and serve new markets. Collaborate with Product, UX, and other engineers to design and develop internal user-facing products. Ship solutions to novel problems that arise in a fast-paced environment. collaborative - work across team boundaries cross-functional - work with PM, UX, legal, operations, or other non-engineering roles independence / leadership - take ownership and drive efforts to completion You have: Bachelor's degree in Computer Science or equivalent practical experience. 4+ years of experience in full-stack development. Strong understanding of web development fundamentals including HTML, CSS, and modern JavaScript/TypeScript. Knowledge of common frontend web development frameworks (e.g., Angular, React, Vue). Interest in backend development. Experience with 3rd party integrations and public APIs We prefer: Familiarity with Google infrastructure (e.g. Flume, Borg, Protocol Buffers, OnePlatform) or GCP equivalent Backend experience in Java, Python, Go, C++ or similar. Working knowledge of frontend frameworks (e.g. Angular, Dart) Scalability experience Experience in the automotive industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $170,000-$216,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's commercial service is up and running in multiple cities, with ambitious plans to expand dramatically in the coming years; the associated infrastructure is in an early stage and requires significant investment for Waymo to grow into a high scale, world-class service. Increasing demand for Waymo's ride-hailing service will drive evolution of our systems, providing an opportunity-rich environment to solve hard, ambiguous, high-impact, cross-functional problems. Team: Fleet Management Project: Workshop management; focused on planning and executing vehicle maintenance and uptime software. In this hybrid role, you will report to an Engineering Manager. You will: Design, develop, test, and optimize Angular applications using Typescript and modern development techniques. Build and evolve mission-critical tools and systems that allow Waymo to scale and serve new markets. Collaborate with Product, UX, and other engineers to design and develop internal user-facing products. Ship solutions to novel problems that arise in a fast-paced environment. collaborative - work across team boundaries cross-functional - work with PM, UX, legal, operations, or other non-engineering roles independence / leadership - take ownership and drive efforts to completion You have: Bachelor's degree in Computer Science or equivalent practical experience. 4+ years of experience in full-stack development. Strong understanding of web development fundamentals including HTML, CSS, and modern JavaScript/TypeScript. Knowledge of common frontend web development frameworks (e.g., Angular, React, Vue). Interest in backend development. Experience with 3rd party integrations and public APIs We prefer: Familiarity with Google infrastructure (e.g. Flume, Borg, Protocol Buffers, OnePlatform) or GCP equivalent Backend experience in Java, Python, Go, C++ or similar. Working knowledge of frontend frameworks (e.g. Angular, Dart) Scalability experience Experience in the automotive industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $170,000-$216,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack. You will: Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a Reinforcement Learning from human preference-based data collection and evaluation system. Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 7+ years of experience with hands-on experience in machine learning projects Strong coding experience in C++ and/or Python. Experience in at least one of: Foundational Models, VLM, Deep Learning Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. 10+ years of experience with hands-on experience in machine learning projects Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack. You will: Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a Reinforcement Learning from human preference-based data collection and evaluation system. Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 7+ years of experience with hands-on experience in machine learning projects Strong coding experience in C++ and/or Python. Experience in at least one of: Foundational Models, VLM, Deep Learning Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. 10+ years of experience with hands-on experience in machine learning projects Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD