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senior machine learning engineer
Sr. Staff AI Engineer
Capital One Mc Lean, Virginia
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)
Capital One New York, New York
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
Capital One New York, New York
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
Capital One Richmond, Virginia
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. Data Integration Engineer
SPS Health LLC Milwaukee, Wisconsin
Summary The Senior Data Integration Engineer is responsible for the design, development, and operation of the data integration and ingestion processes that deliver partner and internal data into our analytics environment. The role owns the flow of data from source acquisition through the curated data warehouse tables consumed by reporting platforms, operational systems, and business analysts. This is a senior, hands-on engineering position spanning the full integration lifecycle: acquiring data from a wide range of external partner and internal systems, validating and conditioning that data on arrival, transforming it into the structures that support analysis and operations, and operating those processes reliably in production. The role is concerned equally with building new integrations and with the continued performance, accuracy, and timeliness of those already in service. A central objective of the position is to advance reusable, well-instrumented integration patterns that shorten the time required to onboard new data sources and that improve the reliability and transparency of data delivery to the business. The Senior Data Integration Engineer will also contribute substantially to the planned modernization of our data platform, evaluating and recommending tooling, architecture, and migration approach for leadership consideration. The role sets technical direction and development standards for data integration work and collaborates closely with data architects, business analysts, stakeholders across the organization, and the technical contacts of our external data partners. Essential Duties and Responsibilities This list of duties and responsibilities is not all inclusive and may be expanded to include other duties and responsibilities as management may deem necessary from time to time. Design, develop, and maintain data integration processes that acquire data from partner and internal sources, including flat file transfers over SFTP, REST API endpoints, and direct database connections. Develop reusable, configuration-driven ingestion patterns that reduce the effort and elapsed time required to onboard new partner data feeds. Develop and maintain the T-SQL transformation logic that carries data from landing and staging layers through to the curated warehouse tables supporting reporting, operational systems, and analyst queries. Design ingestion processes to be idempotent and safely re-runnable, incorporating automated retry and restart behavior for failed executions. Implement automated validation and quarantine processes so that records failing business-defined quality rules are isolated, reported, and prevented from reaching downstream consumers. Implement data quality rules defined by the business, including schema validation, reconciliation, row count and threshold checks, and anomaly detection. Establish monitoring, logging, and alerting for pipeline execution state, data freshness, and load completion, and automate the communication of ingestion status to stakeholders. Diagnose and resolve production data incidents, determine root cause, coordinate remediation, and document preventive measures through runbooks and post-incident review. Contribute to dimensional data model design in collaboration with the data architect and senior team members. Establish and maintain version control, code review, and repeatable deployment practices for database and pipeline code. Define and uphold development standards for data integration work through code review and technical guidance. Evaluate and recommend tooling, architecture, and sequencing for the platform modernization effort for leadership consideration. Migrate established integration workflows to modernized patterns incrementally and without disruption to production operations. Maintain documentation of data feeds, dependencies, lineage, ownership, and escalation paths. Perform all work involving protected health information in accordance with HIPAA requirements, including least-privilege access, secure transmission and storage of partner data, and the exclusion of PHI from logs and non-production environments. Coordinate with partner technical contacts, as needed, to resolve file format, schema, and connectivity questions. Provide occasional off-hours support for critical data load failures or production support rotations as needed to support timely response to critical data issues. Support AI and machine learning initiatives by maintaining reliable, secure, and well-governed data pipelines and datasets used for model development, testing, deployment, monitoring, and ongoing performance evaluation. Maintain confidentiality of information processed & follow company policies and procedures. Qualifications Requires six (6) or more years of professional data engineering, data operations, data platform operations, or related experience. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent professional experience preferred. Experience leading teams and developing supervisory staff preferred. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Other qualifications include: Advanced T-SQL development skills, including: Set-based rewriting of row-by-row and cursor-based logic. MERGE, upsert, and slowly changing dimension load patterns. Window functions and complex analytic queries. Execution plan analysis, index strategy, statistics management, and resolution of performance issues such as parameter sniffing. Transaction management and structured error handling within stored procedures, including correct rollback behavior on partial failure. Demonstrated proficiency in Python for data engineering applications, including API-based data acquisition, file parsing and format handling, data validation, and the development of packaged, scheduled jobs. Familiarity with common data libraries such as requests and pandas is expected. Demonstrated experience acquiring and integrating data from heterogeneous sources, including delimited, fixed-width, JSON, and XML file formats; REST APIs requiring authentication, pagination, and rate-limit handling; and direct database connectivity. Proficiency with Git and collaborative development workflows, including branching, pull requests, and code review. A code-first development approach, with integration logic authored and maintained in T-SQL and Python under source control. Ability to analyze pipeline and query performance and to improve the reliability, scalability, and cost efficiency of data workloads. Strong written communication skills, with the ability to produce runbooks, technical documentation, and incident reports, and to convey the business impact of technical issues to non-technical stakeholders. Strong problem-solving skills, attention to detail, and demonstrated ownership of production systems. Experience with Microsoft Azure data services such as Azure Data Factory or Microsoft Fabric, or comparable cloud orchestration platforms. Experience migrating on-premises SQL Server integration workloads to a cloud platform. Experience with dimensional modeling and data warehouse design. Experience designing and rationalizing SQL Server Agent job dependencies and scheduling. Experience establishing version control, code review, and repeatable deployment practices for database code. Experience implementing CI/CD pipelines for database projects. Experience handling protected health information under HIPAA, or comparably regulated data under an equivalent framework preferred. Experience with healthcare or pharmacy data, including claims, eligibility, prescription, or delivery data preferred. Familiarity with data governance, metadata management, and data lineage practices. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. (The phrases "occasionally," "regularly," and "frequently" correspond to the following definitions: "Occasionally" means up to 1/3 of working time, "regularly" means between 1/3 and 2/3 of working time, and "frequently" means 2/3 and more working time.) While performing the duties of this job, the employee is frequently required to sit; talk or hear; and use hands to handle, or touch objects or controls. The employee is regularly required to stand and walk. On occasion the incumbent may be required to stoop, bend or reach above the shoulders. The employee would rarely need to lift up to 25 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. Work Environment The position is a hybrid position with 2 - 3 days office presence in Milwaukee, WI required. The colleague may perform work-related travel on rare occasions (less than 10%) with an emphasis on travel for impact. . click apply for full job details
09/23/2026
Full time
Summary The Senior Data Integration Engineer is responsible for the design, development, and operation of the data integration and ingestion processes that deliver partner and internal data into our analytics environment. The role owns the flow of data from source acquisition through the curated data warehouse tables consumed by reporting platforms, operational systems, and business analysts. This is a senior, hands-on engineering position spanning the full integration lifecycle: acquiring data from a wide range of external partner and internal systems, validating and conditioning that data on arrival, transforming it into the structures that support analysis and operations, and operating those processes reliably in production. The role is concerned equally with building new integrations and with the continued performance, accuracy, and timeliness of those already in service. A central objective of the position is to advance reusable, well-instrumented integration patterns that shorten the time required to onboard new data sources and that improve the reliability and transparency of data delivery to the business. The Senior Data Integration Engineer will also contribute substantially to the planned modernization of our data platform, evaluating and recommending tooling, architecture, and migration approach for leadership consideration. The role sets technical direction and development standards for data integration work and collaborates closely with data architects, business analysts, stakeholders across the organization, and the technical contacts of our external data partners. Essential Duties and Responsibilities This list of duties and responsibilities is not all inclusive and may be expanded to include other duties and responsibilities as management may deem necessary from time to time. Design, develop, and maintain data integration processes that acquire data from partner and internal sources, including flat file transfers over SFTP, REST API endpoints, and direct database connections. Develop reusable, configuration-driven ingestion patterns that reduce the effort and elapsed time required to onboard new partner data feeds. Develop and maintain the T-SQL transformation logic that carries data from landing and staging layers through to the curated warehouse tables supporting reporting, operational systems, and analyst queries. Design ingestion processes to be idempotent and safely re-runnable, incorporating automated retry and restart behavior for failed executions. Implement automated validation and quarantine processes so that records failing business-defined quality rules are isolated, reported, and prevented from reaching downstream consumers. Implement data quality rules defined by the business, including schema validation, reconciliation, row count and threshold checks, and anomaly detection. Establish monitoring, logging, and alerting for pipeline execution state, data freshness, and load completion, and automate the communication of ingestion status to stakeholders. Diagnose and resolve production data incidents, determine root cause, coordinate remediation, and document preventive measures through runbooks and post-incident review. Contribute to dimensional data model design in collaboration with the data architect and senior team members. Establish and maintain version control, code review, and repeatable deployment practices for database and pipeline code. Define and uphold development standards for data integration work through code review and technical guidance. Evaluate and recommend tooling, architecture, and sequencing for the platform modernization effort for leadership consideration. Migrate established integration workflows to modernized patterns incrementally and without disruption to production operations. Maintain documentation of data feeds, dependencies, lineage, ownership, and escalation paths. Perform all work involving protected health information in accordance with HIPAA requirements, including least-privilege access, secure transmission and storage of partner data, and the exclusion of PHI from logs and non-production environments. Coordinate with partner technical contacts, as needed, to resolve file format, schema, and connectivity questions. Provide occasional off-hours support for critical data load failures or production support rotations as needed to support timely response to critical data issues. Support AI and machine learning initiatives by maintaining reliable, secure, and well-governed data pipelines and datasets used for model development, testing, deployment, monitoring, and ongoing performance evaluation. Maintain confidentiality of information processed & follow company policies and procedures. Qualifications Requires six (6) or more years of professional data engineering, data operations, data platform operations, or related experience. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent professional experience preferred. Experience leading teams and developing supervisory staff preferred. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Other qualifications include: Advanced T-SQL development skills, including: Set-based rewriting of row-by-row and cursor-based logic. MERGE, upsert, and slowly changing dimension load patterns. Window functions and complex analytic queries. Execution plan analysis, index strategy, statistics management, and resolution of performance issues such as parameter sniffing. Transaction management and structured error handling within stored procedures, including correct rollback behavior on partial failure. Demonstrated proficiency in Python for data engineering applications, including API-based data acquisition, file parsing and format handling, data validation, and the development of packaged, scheduled jobs. Familiarity with common data libraries such as requests and pandas is expected. Demonstrated experience acquiring and integrating data from heterogeneous sources, including delimited, fixed-width, JSON, and XML file formats; REST APIs requiring authentication, pagination, and rate-limit handling; and direct database connectivity. Proficiency with Git and collaborative development workflows, including branching, pull requests, and code review. A code-first development approach, with integration logic authored and maintained in T-SQL and Python under source control. Ability to analyze pipeline and query performance and to improve the reliability, scalability, and cost efficiency of data workloads. Strong written communication skills, with the ability to produce runbooks, technical documentation, and incident reports, and to convey the business impact of technical issues to non-technical stakeholders. Strong problem-solving skills, attention to detail, and demonstrated ownership of production systems. Experience with Microsoft Azure data services such as Azure Data Factory or Microsoft Fabric, or comparable cloud orchestration platforms. Experience migrating on-premises SQL Server integration workloads to a cloud platform. Experience with dimensional modeling and data warehouse design. Experience designing and rationalizing SQL Server Agent job dependencies and scheduling. Experience establishing version control, code review, and repeatable deployment practices for database code. Experience implementing CI/CD pipelines for database projects. Experience handling protected health information under HIPAA, or comparably regulated data under an equivalent framework preferred. Experience with healthcare or pharmacy data, including claims, eligibility, prescription, or delivery data preferred. Familiarity with data governance, metadata management, and data lineage practices. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. (The phrases "occasionally," "regularly," and "frequently" correspond to the following definitions: "Occasionally" means up to 1/3 of working time, "regularly" means between 1/3 and 2/3 of working time, and "frequently" means 2/3 and more working time.) While performing the duties of this job, the employee is frequently required to sit; talk or hear; and use hands to handle, or touch objects or controls. The employee is regularly required to stand and walk. On occasion the incumbent may be required to stoop, bend or reach above the shoulders. The employee would rarely need to lift up to 25 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. Work Environment The position is a hybrid position with 2 - 3 days office presence in Milwaukee, WI required. The colleague may perform work-related travel on rare occasions (less than 10%) with an emphasis on travel for impact. . click apply for full job details
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning)
Capital One Mc Lean, Virginia
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).
Channel Applications Engineer, VFDs - FL, GA, SC, AL
ABB
This job is with ABB, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At ABB , we help industries run leaner and cleaner-and every person here makes that happen. You'll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world. This position reports to: Lead Senior Channel Applications Enginee The Channel Applications Engineer (CAE) will provide technical sales execution to the Channel team, Channel partners, technical support, product engineering, R&D and the end customers. The areas of technical sales execution include but are not limited to; ABB Low Voltage (LV) drive & PLC/HMI product knowledge, LV drive & PLC/HMI product application and general LV drive and motor application issues. While this role can be based remotely, the selected candidate will need to reside in either Alabama, Georgia, South Carolina, or Florida . You will be mainly accountable for: Apply Technical Knowledge - Design and recommend tailored solutions based on a deep knowledge of the portfolio and capabilities to meet customers' unique needs. Contribute to specification by negotiating deviations and agreeing on win-win solutions. Identify and communicate applicability of (new/emerging) functional solutions to address current business issues. Advise others on the delivery of high-quality solutions by applying broad and deep professional expertise. Customer Relations - Continuously strengthen existing customer relationships. Take the initiative to get to know new customers. Follow-up on customer complaints in a timely manner according to a defined process. Identify and meet customer needs and ask for feedback. Sales Techniques - Know and confidently use basic sales techniques (e.g. communication, active listening, presentation ). Take different viewpoints into consideration when creating a solution. Self-reflect on sales approach and adjust to customers as needed. Support the Channel team with customer presentations and demonstrations by serving as the product expert through strong solution competence. Analyze drive, PLC/HMI motor application problems and initiate effective measures for their solution. Coordinate activities with related groups to most efficiently achieve objectives to ensure customer satisfaction. Qualifications for the role: Bachelor's degree in electrical engineering or related field. 8+ years of experience in the application of Low Voltage drives with basic knowledge of Compressors, Pump & Fan, Extruder, Crane, Hoists & Winches, Centrifuge, General Machinery and other applications. Exceptional technical application and technical communication skills. Understanding of Serial and Ethernet communication protocols (Ethernet/IP, ProfiNet, Etc). Programming experience in industrial PLCs (ABB, Rockwell, Siemens, Square D, or others). Ability to read, analyze, and interpret electrical and mechanical drawings, common technical journals, financial reports, and legal documents. Ability to respond to common inquiries or complaints from customers, vendors, regulatory agencies, or members of the business community Requires a valid driver's license and passport with ability to travel within the territory (Florida, Georgia, South Carolina, Alabama) > 50% of the time to customer and end user sites. Candidate must already possess a work authorization that would allow them to legally work for ABB in the United States. More about us ABB Drive Products serves the industries and infrastructure segments with world-class drives and programmable logic controllers (PLC). With its products, global scale and local presence, the Division helps customers to improve energy efficiency, productivity and safety. What's in it for you? We empower you to take the lead, share bold ideas, and shape real outcomes. You'll grow through hands-on experience, mentorship, and learning that fits your goals. Here, your work doesn't just matter, it moves things forward. ABB is an Equal Employment Opportunity and Affirmative Action employer for protected Veterans and Individuals with Disabilities at ABB. All qualified applicants will receive consideration for employment without regard to their- sex (gender identity, gender expression, sexual orientation), marital status, citizenship, age, race and ethnicity, inclusive of traits historically associated with race or ethnicity, including but not limited to hair texture and protective hairstyles, color, religious creed, national origin, pregnancy, physical or mental disability, genetic information, protected Veteran status, or any other characteristic protected by federal and state law. For more information regarding your (EEO) rights as an applicant, please visit the following websites: As an Equal Employment Opportunity and Affirmative Action Employer for Protected Veterans and Individuals with Disabilities, applicants may request to review the plan of a particular ABB facility between the hours of 9:00 A.M. - 5:00 P.M. EST Monday through Friday by contacting an ABB HR Representative at 1-. Protected Veterans and Individuals with Disabilities may request a reasonable accommodation if you are unable or limited in your ability to use or access ABB's career site as a result of your disability. You may request reasonable accommodations by calling an ABB HR Representative at 1- or by sending an email to . Resumes and applications will not be accepted in this manner. While base salary is determined by things such as the successful applicant's qualifications and experience, this position is expected to pay between $100,500 and $160,800 annually and is bonus eligible. ABB Benefit Summary for eligible US employees excludes ABB E-mobility, Athens union, Puerto Rico Go to and click on "Candidate/Guest" to learn more Health, Life & Disability Choice between two medical plan options: A PPO plan called the Copay Plan OR a High Deductible Health Plan (with a Health Savings Account) called the High Deductible Plan. Choice between two dental plan options: Core and Core Plus Vision benefit Company paid life insurance (2X base pay) Company paid AD&D (1X base pay) Voluntary life and AD&D - 100% employee paid up to maximums Short Term Disability - up to 26 weeks - Company paid Long Term Disability - 60% of pay - Company paid. Ability to "buy-up" to 66 2/3% of pay. Supplemental benefits - 100% employee paid (Accident insurance, hospital indemnity, critical illness, pet insurance Parental Leave - up to 6 weeks Employee Assistance Program Health Advocate support resources for mental/behavioral health, general health navigation and virtual health, and infertility/adoption Employee discount program Retirement 401k Savings Plan with Company Contributions Employee Stock Acquisition Plan (ESAP) Time off ABB provides 11 paid holidays. Salaried exempt positions are provided vacation under a permissive time away policy. Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That's why we welcome people from all backgrounds and experiences. Ready to make an impact? Apply today or visit to learn more about the impact of our solutions across the globe.
09/23/2026
Full time
This job is with ABB, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At ABB , we help industries run leaner and cleaner-and every person here makes that happen. You'll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world. This position reports to: Lead Senior Channel Applications Enginee The Channel Applications Engineer (CAE) will provide technical sales execution to the Channel team, Channel partners, technical support, product engineering, R&D and the end customers. The areas of technical sales execution include but are not limited to; ABB Low Voltage (LV) drive & PLC/HMI product knowledge, LV drive & PLC/HMI product application and general LV drive and motor application issues. While this role can be based remotely, the selected candidate will need to reside in either Alabama, Georgia, South Carolina, or Florida . You will be mainly accountable for: Apply Technical Knowledge - Design and recommend tailored solutions based on a deep knowledge of the portfolio and capabilities to meet customers' unique needs. Contribute to specification by negotiating deviations and agreeing on win-win solutions. Identify and communicate applicability of (new/emerging) functional solutions to address current business issues. Advise others on the delivery of high-quality solutions by applying broad and deep professional expertise. Customer Relations - Continuously strengthen existing customer relationships. Take the initiative to get to know new customers. Follow-up on customer complaints in a timely manner according to a defined process. Identify and meet customer needs and ask for feedback. Sales Techniques - Know and confidently use basic sales techniques (e.g. communication, active listening, presentation ). Take different viewpoints into consideration when creating a solution. Self-reflect on sales approach and adjust to customers as needed. Support the Channel team with customer presentations and demonstrations by serving as the product expert through strong solution competence. Analyze drive, PLC/HMI motor application problems and initiate effective measures for their solution. Coordinate activities with related groups to most efficiently achieve objectives to ensure customer satisfaction. Qualifications for the role: Bachelor's degree in electrical engineering or related field. 8+ years of experience in the application of Low Voltage drives with basic knowledge of Compressors, Pump & Fan, Extruder, Crane, Hoists & Winches, Centrifuge, General Machinery and other applications. Exceptional technical application and technical communication skills. Understanding of Serial and Ethernet communication protocols (Ethernet/IP, ProfiNet, Etc). Programming experience in industrial PLCs (ABB, Rockwell, Siemens, Square D, or others). Ability to read, analyze, and interpret electrical and mechanical drawings, common technical journals, financial reports, and legal documents. Ability to respond to common inquiries or complaints from customers, vendors, regulatory agencies, or members of the business community Requires a valid driver's license and passport with ability to travel within the territory (Florida, Georgia, South Carolina, Alabama) > 50% of the time to customer and end user sites. Candidate must already possess a work authorization that would allow them to legally work for ABB in the United States. More about us ABB Drive Products serves the industries and infrastructure segments with world-class drives and programmable logic controllers (PLC). With its products, global scale and local presence, the Division helps customers to improve energy efficiency, productivity and safety. What's in it for you? We empower you to take the lead, share bold ideas, and shape real outcomes. You'll grow through hands-on experience, mentorship, and learning that fits your goals. Here, your work doesn't just matter, it moves things forward. ABB is an Equal Employment Opportunity and Affirmative Action employer for protected Veterans and Individuals with Disabilities at ABB. All qualified applicants will receive consideration for employment without regard to their- sex (gender identity, gender expression, sexual orientation), marital status, citizenship, age, race and ethnicity, inclusive of traits historically associated with race or ethnicity, including but not limited to hair texture and protective hairstyles, color, religious creed, national origin, pregnancy, physical or mental disability, genetic information, protected Veteran status, or any other characteristic protected by federal and state law. For more information regarding your (EEO) rights as an applicant, please visit the following websites: As an Equal Employment Opportunity and Affirmative Action Employer for Protected Veterans and Individuals with Disabilities, applicants may request to review the plan of a particular ABB facility between the hours of 9:00 A.M. - 5:00 P.M. EST Monday through Friday by contacting an ABB HR Representative at 1-. Protected Veterans and Individuals with Disabilities may request a reasonable accommodation if you are unable or limited in your ability to use or access ABB's career site as a result of your disability. You may request reasonable accommodations by calling an ABB HR Representative at 1- or by sending an email to . Resumes and applications will not be accepted in this manner. While base salary is determined by things such as the successful applicant's qualifications and experience, this position is expected to pay between $100,500 and $160,800 annually and is bonus eligible. ABB Benefit Summary for eligible US employees excludes ABB E-mobility, Athens union, Puerto Rico Go to and click on "Candidate/Guest" to learn more Health, Life & Disability Choice between two medical plan options: A PPO plan called the Copay Plan OR a High Deductible Health Plan (with a Health Savings Account) called the High Deductible Plan. Choice between two dental plan options: Core and Core Plus Vision benefit Company paid life insurance (2X base pay) Company paid AD&D (1X base pay) Voluntary life and AD&D - 100% employee paid up to maximums Short Term Disability - up to 26 weeks - Company paid Long Term Disability - 60% of pay - Company paid. Ability to "buy-up" to 66 2/3% of pay. Supplemental benefits - 100% employee paid (Accident insurance, hospital indemnity, critical illness, pet insurance Parental Leave - up to 6 weeks Employee Assistance Program Health Advocate support resources for mental/behavioral health, general health navigation and virtual health, and infertility/adoption Employee discount program Retirement 401k Savings Plan with Company Contributions Employee Stock Acquisition Plan (ESAP) Time off ABB provides 11 paid holidays. Salaried exempt positions are provided vacation under a permissive time away policy. Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That's why we welcome people from all backgrounds and experiences. Ready to make an impact? Apply today or visit to learn more about the impact of our solutions across the globe.
Senior/Staff ML Engineer, 3D/4D World Modeling, Simulation
Waymo Mountain View, California
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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. 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 $213,000-$263,000 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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. 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 $213,000-$263,000 USD
GCC Compiler Engineer
Tenstorrent Santa Clara, California
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.
Staff Software Engineer, Simulator Platform
Waymo Mountain View, California
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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Your team will be a diverse, and collaborative group of machine learning (ML) engineers, software engineers and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. We achieve those goals by jointly modeling the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions, and the full sensor suite including camera, Lidar and radars. To increase the fidelity, scalability and controllability of our simulations,we employ the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on large-scale datasets with both generative and reconstructive technologies, as well as traditional rendering approaches. In this hybrid role, you will report to a Senior Staff Engineering Manager. You will: Work closely with onboard and research engineers to scale simulation and enable critical Waymo milestones Support development, testing and evolution of mapping data in the simulator Improve / monitor the performance, scalability and the reliability of the simulator Design the long term architecture to fit the product to an increasing number of internal customers You have: Hands-on experience building a popular (internal- or external-facing) product. Experience on backend knowledge such as workflows, databases, SQL, production monitoring, etc. Strong in C++. We prefer: Experience with the release of software in a highly distributed heterogeneous execution environment Experience with systems programming (game engines, database, OS, distributed) Experience with ML Previous TL experience 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 $251,000-$310,000 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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Your team will be a diverse, and collaborative group of machine learning (ML) engineers, software engineers and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. We achieve those goals by jointly modeling the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions, and the full sensor suite including camera, Lidar and radars. To increase the fidelity, scalability and controllability of our simulations,we employ the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on large-scale datasets with both generative and reconstructive technologies, as well as traditional rendering approaches. In this hybrid role, you will report to a Senior Staff Engineering Manager. You will: Work closely with onboard and research engineers to scale simulation and enable critical Waymo milestones Support development, testing and evolution of mapping data in the simulator Improve / monitor the performance, scalability and the reliability of the simulator Design the long term architecture to fit the product to an increasing number of internal customers You have: Hands-on experience building a popular (internal- or external-facing) product. Experience on backend knowledge such as workflows, databases, SQL, production monitoring, etc. Strong in C++. We prefer: Experience with the release of software in a highly distributed heterogeneous execution environment Experience with systems programming (game engines, database, OS, distributed) Experience with ML Previous TL experience 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 $251,000-$310,000 USD
Oracle
Principal Modern Planner
Oracle Nashville, Tennessee
We are looking for a Principal Modern Planner to own demand planning and forecasting for networking hardware supporting large-scale cloud data center builds and expansions. This role will connect data center build plans, network architecture, product roadmaps, engineering changes, BOMs, and historical demand to a long-range view of hardware requirements. The planner will work across Networking Engineering, Network Architecture, Data Center Planning, Product, Supply Chain, Procurement, Finance, and Data/Analytics to understand the underlying demand drivers, reconcile different inputs, and improve the quality and consistency of the demand plan. The role also has a strong analytics and data component. The successful candidate will use forecasting, statistical analysis, data modeling, automation, and AI/ML to improve planning processes, identify issues in the demand signal, and provide better visibility into future capacity and supply requirements. This is a hands-on Principal role for someone who can move between planning strategy, detailed data analysis, and networking hardware fundamentals, and who can work effectively with both technical teams and senior leadership. Responsibilities Own demand planning and forecasting for networking hardware supporting data center builds, expansions, and ongoing capacity requirements. Develop and maintain long-range demand forecasts, including 24+ month outlooks, across networking products, platforms, and SKUs. Work with Data Center Planning, Network Engineering, Product, Supply Chain, Procurement, and Finance to understand upcoming builds, deployment timing, architecture changes, and other demand drivers. Translate data center build plans and network architecture requirements into hardware and component demand, including the relationship between capacity, racks, network topology, BOMs, and SKUs. Develop forecasting models using historical demand, deployment trends, engineering inputs, product roadmaps, and other relevant signals. Build scenarios to understand the demand impact of changes in data center build timing, network architecture, product transitions, capacity plans, and supply constraints. Work with engineering teams to incorporate BOM changes, new product introductions, product transitions, substitutions, and EOL/EOS plans into the forecast. Identify issues in the demand signal, including double counting, overlapping assumptions, missing requirements, and inconsistent inputs across planning processes. Establish metrics and analytical methods to measure forecast accuracy, bias, volatility, and confidence, and use those insights to improve the planning process. Build and maintain the data and analytical foundation needed to connect data center plans, deployment information, engineering/BOM data, demand, supply, and inventory. Automate recurring planning, reconciliation, and reporting processes using SQL, Python, and other analytical technologies. Apply statistical forecasting, machine learning, optimization, simulation, and AI where they can materially improve planning quality or reduce manual work. Establish a regular planning cadence with engineering and business partners, including mechanisms for reviewing assumptions, reconciling changes, and obtaining alignment on the demand plan. Prepare analysis and recommendations for senior leadership on demand changes, capacity requirements, supply risks, and key planning assumptions. Lead complex planning issues across organizational boundaries and drive them to resolution. Mentor other planners and analytical team members and help establish scalable planning practices. Required Qualifications Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, Supply Chain, Economics, or a related field. 5-8 years of experience in demand planning, forecasting, capacity planning, supply-chain planning, analytics, operations research, or a related area. Experience working with technology hardware, networking, semiconductor, cloud infrastructure, or data center infrastructure. Strong understanding of demand forecasting and long-range planning, including forecast accuracy, bias, scenario planning, and demand drivers. Experience working with complex hardware products, including BOMs, SKUs, product lifecycle, NPI, EOL/EOS, and product transitions. Experience connecting engineering, deployment, or infrastructure plans to hardware demand. Strong analytical and quantitative skills, including hands-on experience with SQL and Python/R. Experience working with large datasets and using data to investigate problems and support planning decisions. Strong cross-functional communication skills and experience working with engineering, supply chain, product, and business stakeholders. Ability to operate independently, navigate ambiguity, and influence decisions across organizations. Preferred Qualifications Experience with data center build and deployment planning or cloud infrastructure capacity planning. Experience with networking hardware such as Ethernet switches, NICs, DPUs/SmartNICs, optical transceivers, cables, or related components. Familiarity with data center networking architectures and high-performance/AI networking. Experience developing models that connect data center builds and network architecture to BOM and SKU-level demand. Experience with networking or semiconductor supply chains, including lead times, constraints, allocation, substitutions, and technology transitions. Experience with time-series forecasting, probabilistic forecasting, machine learning, optimization, simulation, or other advanced analytical methods. Experience building data pipelines, analytical datasets, dashboards, or planning tools. Experience using GenAI or automation to improve planning and forecasting processes. Experience presenting planning analysis and recommendations to senior engineering or business leadership. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $90,100 to $209,500 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process . click apply for full job details
09/23/2026
Full time
We are looking for a Principal Modern Planner to own demand planning and forecasting for networking hardware supporting large-scale cloud data center builds and expansions. This role will connect data center build plans, network architecture, product roadmaps, engineering changes, BOMs, and historical demand to a long-range view of hardware requirements. The planner will work across Networking Engineering, Network Architecture, Data Center Planning, Product, Supply Chain, Procurement, Finance, and Data/Analytics to understand the underlying demand drivers, reconcile different inputs, and improve the quality and consistency of the demand plan. The role also has a strong analytics and data component. The successful candidate will use forecasting, statistical analysis, data modeling, automation, and AI/ML to improve planning processes, identify issues in the demand signal, and provide better visibility into future capacity and supply requirements. This is a hands-on Principal role for someone who can move between planning strategy, detailed data analysis, and networking hardware fundamentals, and who can work effectively with both technical teams and senior leadership. Responsibilities Own demand planning and forecasting for networking hardware supporting data center builds, expansions, and ongoing capacity requirements. Develop and maintain long-range demand forecasts, including 24+ month outlooks, across networking products, platforms, and SKUs. Work with Data Center Planning, Network Engineering, Product, Supply Chain, Procurement, and Finance to understand upcoming builds, deployment timing, architecture changes, and other demand drivers. Translate data center build plans and network architecture requirements into hardware and component demand, including the relationship between capacity, racks, network topology, BOMs, and SKUs. Develop forecasting models using historical demand, deployment trends, engineering inputs, product roadmaps, and other relevant signals. Build scenarios to understand the demand impact of changes in data center build timing, network architecture, product transitions, capacity plans, and supply constraints. Work with engineering teams to incorporate BOM changes, new product introductions, product transitions, substitutions, and EOL/EOS plans into the forecast. Identify issues in the demand signal, including double counting, overlapping assumptions, missing requirements, and inconsistent inputs across planning processes. Establish metrics and analytical methods to measure forecast accuracy, bias, volatility, and confidence, and use those insights to improve the planning process. Build and maintain the data and analytical foundation needed to connect data center plans, deployment information, engineering/BOM data, demand, supply, and inventory. Automate recurring planning, reconciliation, and reporting processes using SQL, Python, and other analytical technologies. Apply statistical forecasting, machine learning, optimization, simulation, and AI where they can materially improve planning quality or reduce manual work. Establish a regular planning cadence with engineering and business partners, including mechanisms for reviewing assumptions, reconciling changes, and obtaining alignment on the demand plan. Prepare analysis and recommendations for senior leadership on demand changes, capacity requirements, supply risks, and key planning assumptions. Lead complex planning issues across organizational boundaries and drive them to resolution. Mentor other planners and analytical team members and help establish scalable planning practices. Required Qualifications Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, Supply Chain, Economics, or a related field. 5-8 years of experience in demand planning, forecasting, capacity planning, supply-chain planning, analytics, operations research, or a related area. Experience working with technology hardware, networking, semiconductor, cloud infrastructure, or data center infrastructure. Strong understanding of demand forecasting and long-range planning, including forecast accuracy, bias, scenario planning, and demand drivers. Experience working with complex hardware products, including BOMs, SKUs, product lifecycle, NPI, EOL/EOS, and product transitions. Experience connecting engineering, deployment, or infrastructure plans to hardware demand. Strong analytical and quantitative skills, including hands-on experience with SQL and Python/R. Experience working with large datasets and using data to investigate problems and support planning decisions. Strong cross-functional communication skills and experience working with engineering, supply chain, product, and business stakeholders. Ability to operate independently, navigate ambiguity, and influence decisions across organizations. Preferred Qualifications Experience with data center build and deployment planning or cloud infrastructure capacity planning. Experience with networking hardware such as Ethernet switches, NICs, DPUs/SmartNICs, optical transceivers, cables, or related components. Familiarity with data center networking architectures and high-performance/AI networking. Experience developing models that connect data center builds and network architecture to BOM and SKU-level demand. Experience with networking or semiconductor supply chains, including lead times, constraints, allocation, substitutions, and technology transitions. Experience with time-series forecasting, probabilistic forecasting, machine learning, optimization, simulation, or other advanced analytical methods. Experience building data pipelines, analytical datasets, dashboards, or planning tools. Experience using GenAI or automation to improve planning and forecasting processes. Experience presenting planning analysis and recommendations to senior engineering or business leadership. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $90,100 to $209,500 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process . click apply for full job details
Senior Customer Enablement AI Programs Manager
Databricks New York, New York
CSQ426R319 Senior Customer Enablement AI Programs Manager As a Senior Customer Enablement AI Programs Manager, you will own the AI strategy and roadmap for the Scaled Customer Enablement Agent Suite - bringing together GTM activation, applied AI, and enablement strategy. You will define how the agents retrieve, reason over, and surface enablement insights to global Account Teams, turning learner and account data into prescriptive, just-in-time recommendations that improve account health and grow the number of trained users across our customer base. By automating GTM processes, you will ensure Account Teams and customers receive consistent Databricks enablement planning resources. You will be responsible for driving the AI roadmap for customer enablement, compounding enablement as a strategic leverage for our customers and for Databricks. This role will report to the Global Customer Enablement Practice Senior Director. This is an exciting opportunity for a motivated and innovative entrepreneur with a passion for working across departments and across regions. The impact you will have: Own the product roadmap and architecture direction for the Scaled Customer Enablement Agent Suite - defining the data inputs, retrieval sources, and agent behaviors that generate enablement recommendations. Lead the rollout and drive field adoption of the Scaled Customer Enablement Agent Suite, delivering automated learning insights and proposals to Account Teams. Structure the enablement knowledge base for retrieval - designing content schemas, metadata, and chunking so agents return accurate, grounded outputs - and maintain the underlying customer enablement playbook. Define the signals and triggers - usage patterns, learning milestones, and account-health thresholds - that prompt the agents to surface a free-to-paid enablement opportunity to Account Teams at the right moment. Partner with technical teams to embed enablement calls-to-action and insights directly into field tools. Define predictive signals and analytics that flag emerging account-health and skills gaps before they impact renewals or consumption, and integrate these into leadership reviews and manager coaching toolkits. Establish evaluation and quality loops for agent outputs - defining what "good" looks like, measuring accuracy and groundedness, and driving iteration with the technical team. What we look for 6+ years of experience in Sales Enablement, GTM Program Management, or Sales Operations in a high-growth SaaS environment. Proven track record of managing complex workstreams and delivering global field motions with measurable adoption. Hands-on fluency with modern AI systems - RAG pipelines, agents, and LLM-powered workflows. You understand how retrieval sources, prompt design, context and data hierarchies, and grounding affect output quality, and can translate that into requirements a technical team can build against. Demonstrated experience owning a product or system area end to end - defining requirements, collaborating with engineering and data teams, and shipping AI-powered capabilities from concept to field adoption. Comfort defining metrics and running experiments - instrumenting agent performance, measuring output quality and field adoption, and using analytics to drive iteration. Exceptional ability to work cross-functionally across Sales, Marketing, and Technical teams to ensure a unified enablement vision. Expert at using data dashboards to track progress and communicate the "business story" behind the numbers (e.g., the link between enabled users and consumption lift). Able to solve ambiguous problems in a fast-moving environment and translate complex strategies into simple, executable field instructions. Familiarity with the education technology or customer training landscape is a significant plus. Familiarity with how enablement and knowledge content must be structured for machine consumption (schemas, metadata, modularity) is a strong plus. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Zone 1 Pay Range $117,400-$161,350 USD Zone 2 Pay Range $105,600-$145,200 USD Zone 3 Pay Range $99,800-$137,150 USD Zone 4 Pay Range $93,900-$129,150 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
09/23/2026
Full time
CSQ426R319 Senior Customer Enablement AI Programs Manager As a Senior Customer Enablement AI Programs Manager, you will own the AI strategy and roadmap for the Scaled Customer Enablement Agent Suite - bringing together GTM activation, applied AI, and enablement strategy. You will define how the agents retrieve, reason over, and surface enablement insights to global Account Teams, turning learner and account data into prescriptive, just-in-time recommendations that improve account health and grow the number of trained users across our customer base. By automating GTM processes, you will ensure Account Teams and customers receive consistent Databricks enablement planning resources. You will be responsible for driving the AI roadmap for customer enablement, compounding enablement as a strategic leverage for our customers and for Databricks. This role will report to the Global Customer Enablement Practice Senior Director. This is an exciting opportunity for a motivated and innovative entrepreneur with a passion for working across departments and across regions. The impact you will have: Own the product roadmap and architecture direction for the Scaled Customer Enablement Agent Suite - defining the data inputs, retrieval sources, and agent behaviors that generate enablement recommendations. Lead the rollout and drive field adoption of the Scaled Customer Enablement Agent Suite, delivering automated learning insights and proposals to Account Teams. Structure the enablement knowledge base for retrieval - designing content schemas, metadata, and chunking so agents return accurate, grounded outputs - and maintain the underlying customer enablement playbook. Define the signals and triggers - usage patterns, learning milestones, and account-health thresholds - that prompt the agents to surface a free-to-paid enablement opportunity to Account Teams at the right moment. Partner with technical teams to embed enablement calls-to-action and insights directly into field tools. Define predictive signals and analytics that flag emerging account-health and skills gaps before they impact renewals or consumption, and integrate these into leadership reviews and manager coaching toolkits. Establish evaluation and quality loops for agent outputs - defining what "good" looks like, measuring accuracy and groundedness, and driving iteration with the technical team. What we look for 6+ years of experience in Sales Enablement, GTM Program Management, or Sales Operations in a high-growth SaaS environment. Proven track record of managing complex workstreams and delivering global field motions with measurable adoption. Hands-on fluency with modern AI systems - RAG pipelines, agents, and LLM-powered workflows. You understand how retrieval sources, prompt design, context and data hierarchies, and grounding affect output quality, and can translate that into requirements a technical team can build against. Demonstrated experience owning a product or system area end to end - defining requirements, collaborating with engineering and data teams, and shipping AI-powered capabilities from concept to field adoption. Comfort defining metrics and running experiments - instrumenting agent performance, measuring output quality and field adoption, and using analytics to drive iteration. Exceptional ability to work cross-functionally across Sales, Marketing, and Technical teams to ensure a unified enablement vision. Expert at using data dashboards to track progress and communicate the "business story" behind the numbers (e.g., the link between enabled users and consumption lift). Able to solve ambiguous problems in a fast-moving environment and translate complex strategies into simple, executable field instructions. Familiarity with the education technology or customer training landscape is a significant plus. Familiarity with how enablement and knowledge content must be structured for machine consumption (schemas, metadata, modularity) is a strong plus. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Zone 1 Pay Range $117,400-$161,350 USD Zone 2 Pay Range $105,600-$145,200 USD Zone 3 Pay Range $99,800-$137,150 USD Zone 4 Pay Range $93,900-$129,150 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Data Scientist
Waymo Remote, Oregon
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. Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology-resulting in denser signals and challenging new problems in estimation and experimental design. In this hybrid role you will report to a data science manager. You will: Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation. Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving. Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods. Derive data-driven conclusions and communicate findings to senior stakeholders. Establish yourself as the point-of-contact for a significant project area by using data to drive technical decisions and demonstrate success. Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo's simulation software; facilitate deployment readiness decisions for both products. Mentor other data scientists and provide constructive technical feedback within the team and across Waymo. You have: Degree in a quantitative field (e.g. Statistics, Mathematics, Physics) 5+ years of industry experience solving data science problems, or a PhD in a quantitative field and 3+ years of industry experience Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: PhD in a quantitative field A demonstrated track record of independently driving data science projects to deliver business value Experience solving problems related to Autonomous Driving or Ride Hailing Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction 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. Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology-resulting in denser signals and challenging new problems in estimation and experimental design. In this hybrid role you will report to a data science manager. You will: Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation. Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving. Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods. Derive data-driven conclusions and communicate findings to senior stakeholders. Establish yourself as the point-of-contact for a significant project area by using data to drive technical decisions and demonstrate success. Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo's simulation software; facilitate deployment readiness decisions for both products. Mentor other data scientists and provide constructive technical feedback within the team and across Waymo. You have: Degree in a quantitative field (e.g. Statistics, Mathematics, Physics) 5+ years of industry experience solving data science problems, or a PhD in a quantitative field and 3+ years of industry experience Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: PhD in a quantitative field A demonstrated track record of independently driving data science projects to deliver business value Experience solving problems related to Autonomous Driving or Ride Hailing Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction 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
Data Scientist
Waymo Remote, Oregon
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. Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology-resulting in denser signals and challenging new problems in estimation and experimental design. In this hybrid role you will report to a Data Science Manager. You will: Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation. Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving. Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc. Frame and solve ambiguous problems, derive data-driven conclusions, and communicate findings to senior stakeholders. Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo's simulation software; facilitate deployment readiness decisions for both products. You have: Degree in a quantitative field (e.g. Statistics, Mathematics, Physics) 3+ years of industry experience solving data science problems or a PhD in a quantitative field Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: PhD in a quantitative field Experience solving problems related to Autonomous Driving or Ride Hailing Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction 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. Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology-resulting in denser signals and challenging new problems in estimation and experimental design. In this hybrid role you will report to a Data Science Manager. You will: Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation. Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving. Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc. Frame and solve ambiguous problems, derive data-driven conclusions, and communicate findings to senior stakeholders. Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo's simulation software; facilitate deployment readiness decisions for both products. You have: Degree in a quantitative field (e.g. Statistics, Mathematics, Physics) 3+ years of industry experience solving data science problems or a PhD in a quantitative field Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: PhD in a quantitative field Experience solving problems related to Autonomous Driving or Ride Hailing Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction 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
Senior Staff ML Engineer, Driver Understanding and Evaluation
Waymo Mountain View, California
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
Tech Lead, Self Driving Eval Infrastructure
Waymo Mountain View, California
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 generates an unprecedented scale and complexity of data from billions of miles driven in simulation, millions on public roads, and the growing commercial operations. At the heart of achieving our mission lies the ability to deeply understand this data. World-class data analysis infrastructure is the bedrock of Waymo's success. It is absolutely critical for: Validating the safety and performance of the Waymo Driver. Accelerating research and development cycles across engineering, including Simulation, Onboard, and Machine Learning. Enabling data-driven decisions for our commercial operations and product strategy. Standardizing how we measure progress and compare performance across different contexts. The insights derived from our data platforms directly influence every aspect of our technology and business. We are looking for an exceptional technical leader to drive the vision and architecture of these vital systems. About the Role: We are seeking an exceptional a Leader to provide technical leadership and architectural vision for the core data platforms that power Waymo's insights and decision-making. This role is pivotal in shaping how Waymo leverages data to understand complex scenarios, measure progress, and ultimately deploy and operate our autonomous technology safely and effectively across the globe. You will be instrumental in tackling some of our most challenging data systems problems, from ensuring metrics consistency to building a scalable single source of truth for our ride-hail commercialization expansion. You will: Lead the architectural design and technical strategy for Waymo's core data platforms, encompassing a "Single Source of Truth" data lake for Commercialization and "Metrics Portability and Standardization" for Driver Evaluations. Establish and enforce comprehensive data governance frameworks across the data ecosystem, enabling easy data discoverability, and enhancing data quality. Identify and address inefficiencies in the data development lifecycle. Drive initiatives to improve developer productivity, streamline workflows, and enhance the overall effectiveness of the data engineering and metrics development functions in Waymo. Serve as a lead technical liaison, collaborating deeply with Simulation, Onboard, ML, and Commercialization teams to understand data needs, define data contracts, translate requirements into technical solutions, and ensure alignment on architectural direction. Mentor senior engineers, guide critical technical decisions, and champion best practices in data engineering, including system reliability, efficiency, developer experience, and innovation to address new challenges. You have: Proven track record of setting technical vision, driving multi-quarter roadmaps, and delivering impactful data projects as a technical lead for senior engineering teams, with demonstrated ability to influence across organizational boundaries. Excellent communication skills, with the ability to articulate complex technical designs, trade-offs, and strategies to diverse stakeholders, including senior leadership and partner engineering, data scientists, and product teams. Extensive experience architecting, building, and operating complex, large-scale distributed data systems (e.g., data lakes, lakehouse, data mesh, streaming platforms, query engines). Deep expertise in designing and implementing data governance principles, including metadata systems, data lineage, data quality frameworks, and data discoverability solutions at scale. Strong experience in designing and evolving data-centric APIs, schemas, and data contracts to ensure system interoperability, portability, and long-term maintainability. Expertise in data pipeline and query engine development and proficiencies in writing both SQL and one of C++/Java/Python code language. We prefer: Familiarity with data from autonomous vehicle operations, logistics, or ride-hailing business domains. Experience with Google's data infrastructure and tools such as F1 Query, Napa, Flume, Plx, or Google Cloud Platform (GCP) data services such as BigQuery, Cloud Dataflow, etc. 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. Waymo generates an unprecedented scale and complexity of data from billions of miles driven in simulation, millions on public roads, and the growing commercial operations. At the heart of achieving our mission lies the ability to deeply understand this data. World-class data analysis infrastructure is the bedrock of Waymo's success. It is absolutely critical for: Validating the safety and performance of the Waymo Driver. Accelerating research and development cycles across engineering, including Simulation, Onboard, and Machine Learning. Enabling data-driven decisions for our commercial operations and product strategy. Standardizing how we measure progress and compare performance across different contexts. The insights derived from our data platforms directly influence every aspect of our technology and business. We are looking for an exceptional technical leader to drive the vision and architecture of these vital systems. About the Role: We are seeking an exceptional a Leader to provide technical leadership and architectural vision for the core data platforms that power Waymo's insights and decision-making. This role is pivotal in shaping how Waymo leverages data to understand complex scenarios, measure progress, and ultimately deploy and operate our autonomous technology safely and effectively across the globe. You will be instrumental in tackling some of our most challenging data systems problems, from ensuring metrics consistency to building a scalable single source of truth for our ride-hail commercialization expansion. You will: Lead the architectural design and technical strategy for Waymo's core data platforms, encompassing a "Single Source of Truth" data lake for Commercialization and "Metrics Portability and Standardization" for Driver Evaluations. Establish and enforce comprehensive data governance frameworks across the data ecosystem, enabling easy data discoverability, and enhancing data quality. Identify and address inefficiencies in the data development lifecycle. Drive initiatives to improve developer productivity, streamline workflows, and enhance the overall effectiveness of the data engineering and metrics development functions in Waymo. Serve as a lead technical liaison, collaborating deeply with Simulation, Onboard, ML, and Commercialization teams to understand data needs, define data contracts, translate requirements into technical solutions, and ensure alignment on architectural direction. Mentor senior engineers, guide critical technical decisions, and champion best practices in data engineering, including system reliability, efficiency, developer experience, and innovation to address new challenges. You have: Proven track record of setting technical vision, driving multi-quarter roadmaps, and delivering impactful data projects as a technical lead for senior engineering teams, with demonstrated ability to influence across organizational boundaries. Excellent communication skills, with the ability to articulate complex technical designs, trade-offs, and strategies to diverse stakeholders, including senior leadership and partner engineering, data scientists, and product teams. Extensive experience architecting, building, and operating complex, large-scale distributed data systems (e.g., data lakes, lakehouse, data mesh, streaming platforms, query engines). Deep expertise in designing and implementing data governance principles, including metadata systems, data lineage, data quality frameworks, and data discoverability solutions at scale. Strong experience in designing and evolving data-centric APIs, schemas, and data contracts to ensure system interoperability, portability, and long-term maintainability. Expertise in data pipeline and query engine development and proficiencies in writing both SQL and one of C++/Java/Python code language. We prefer: Familiarity with data from autonomous vehicle operations, logistics, or ride-hailing business domains. Experience with Google's data infrastructure and tools such as F1 Query, Napa, Flume, Plx, or Google Cloud Platform (GCP) data services such as BigQuery, Cloud Dataflow, etc. 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
Senior Software Engineer, Quantitative Evaluations
Waymo Mountain View, California
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
Senior Software Engineer, Quantitative Evaluations
Waymo San Francisco, California
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
Staff Machine Learning Engineer(TLM), Driver Understanding and Evaluation
Waymo Mountain View, California
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
Staff Technical Lead Manager, Simulation, Machine Learning
Waymo Mountain View, California
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

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