The Opportunity insitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human platform identifies novel, high-impact genetic intervention points, which our TherML platform translates into therapeutics-whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point. To enable that mission, we need a software layer that ties together the scientific, automation, and machine learning platforms - that's our Lab Platform: a harness for science, built as an agentic workflow system that lets scientists drive the lab through an agent. Our bar is that everything in the lab should be agentically accessible (any action a scientist can take, an agent can take), agentically legible (agents understand what the data means in insitro's context, not just how to fetch it), and humanly verifiable (a scientist can always check what an agent did and why). This is real robotics, workflow automation, and applied agent tooling - and your users are in the building with you. You'll work across the stack - front end, backend, and the integrations that reach into instruments, Benchling, and agent runtimes - partnering closely with our machine learning, automation, and biology teams. Based in South San Francisco, this role reports directly to Senior Manager, Software Engineering and offers an in-person hybrid schedule of three days per week. We'll bring you up to speed in the domain of drug development and back your ideas with real trust and mentorship along the way. Responsibilities Full-Stack Ownership Ship Across the Stack: Build the React and TypeScript frontends scientists use every day, the Python services behind them, and integrations that reach instruments, Benchling, and agent runtimes Own It End to End: Take a feature from the first conversation with a scientist through the data model and UI to the alert that fires when it breaks Do the Normal SWE Things: Write code, review design docs, talk to users, and do code reviews that actually make the codebase better Agentic Tooling & Experimentation Chase User Appreciation: Ship things that make scientists say "OMG, this is amazing, thank you so much." Figure Out What's Actually Useful: Test agentic tooling ideas through prototypes, real users, and short iterative loops rather than betting on theory Move the Needle: Contribute work that meaningfully advances insitro's mission and the pace of drug development Cross-Functional Partnership Go Watch the Work: Spend time in the lab observing the workflow before you change it Partner Broadly: Collaborate closely with machine learning, automation, and biology teams to build tools people actually use Keep Humans in the Loop: Design for provenance and verifiability, so a scientist can always check what an agent did and why About You Experience & Qualifications Tenure: 2-4+ years of experience as a professional software engineer Engineering Fundamentals: Working knowledge of AWS or GCP, relational databases, and standard practices like version control and code review Core Competencies Product Instinct: You think like a product person - you want to know who the user is, what they're actually trying to do, and you have opinions about what to build Curious About the Science: You don't need a biology background, but you want to learn the domain rather than treat it as someone else's problem Comfortable in the Gray Area: You can reason clearly about the tradeoffs between quality and speed Fits the Team: You're up for writing design docs, having opinions in code review, and yes, goofing around on Slack. Preferred Qualifications Domain Experience: Experience with LIMS, lab automation, or another life sciences domain Agent/LLM Experience: Experience building with LLMs or agent frameworks - tool and skill design, evaluation, or getting a model to behave reliably against real systems Stack Familiarity: Experience with Django, FastAPI, SQLAlchemy, React, TypeScript, PostgreSQL, Docker, or AWS Compensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $111,000 - $140,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: 401(k) plan with employer matching for contributions Excellent medical, dental, and vision coverage as well as mental health and well-being support Open, flexible vacation policy Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc) Quarterly budget for books and online courses for self-development New hire stipend for home office setup Monthly cell phone & internet stipend Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams-grounded in a wide range of expertise and life experiences-and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process. Please be aware of recruitment scams: we never request payments, all recruitment communications are , and if in doubt, contact us at . About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit .
09/24/2026
Full time
The Opportunity insitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human platform identifies novel, high-impact genetic intervention points, which our TherML platform translates into therapeutics-whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point. To enable that mission, we need a software layer that ties together the scientific, automation, and machine learning platforms - that's our Lab Platform: a harness for science, built as an agentic workflow system that lets scientists drive the lab through an agent. Our bar is that everything in the lab should be agentically accessible (any action a scientist can take, an agent can take), agentically legible (agents understand what the data means in insitro's context, not just how to fetch it), and humanly verifiable (a scientist can always check what an agent did and why). This is real robotics, workflow automation, and applied agent tooling - and your users are in the building with you. You'll work across the stack - front end, backend, and the integrations that reach into instruments, Benchling, and agent runtimes - partnering closely with our machine learning, automation, and biology teams. Based in South San Francisco, this role reports directly to Senior Manager, Software Engineering and offers an in-person hybrid schedule of three days per week. We'll bring you up to speed in the domain of drug development and back your ideas with real trust and mentorship along the way. Responsibilities Full-Stack Ownership Ship Across the Stack: Build the React and TypeScript frontends scientists use every day, the Python services behind them, and integrations that reach instruments, Benchling, and agent runtimes Own It End to End: Take a feature from the first conversation with a scientist through the data model and UI to the alert that fires when it breaks Do the Normal SWE Things: Write code, review design docs, talk to users, and do code reviews that actually make the codebase better Agentic Tooling & Experimentation Chase User Appreciation: Ship things that make scientists say "OMG, this is amazing, thank you so much." Figure Out What's Actually Useful: Test agentic tooling ideas through prototypes, real users, and short iterative loops rather than betting on theory Move the Needle: Contribute work that meaningfully advances insitro's mission and the pace of drug development Cross-Functional Partnership Go Watch the Work: Spend time in the lab observing the workflow before you change it Partner Broadly: Collaborate closely with machine learning, automation, and biology teams to build tools people actually use Keep Humans in the Loop: Design for provenance and verifiability, so a scientist can always check what an agent did and why About You Experience & Qualifications Tenure: 2-4+ years of experience as a professional software engineer Engineering Fundamentals: Working knowledge of AWS or GCP, relational databases, and standard practices like version control and code review Core Competencies Product Instinct: You think like a product person - you want to know who the user is, what they're actually trying to do, and you have opinions about what to build Curious About the Science: You don't need a biology background, but you want to learn the domain rather than treat it as someone else's problem Comfortable in the Gray Area: You can reason clearly about the tradeoffs between quality and speed Fits the Team: You're up for writing design docs, having opinions in code review, and yes, goofing around on Slack. Preferred Qualifications Domain Experience: Experience with LIMS, lab automation, or another life sciences domain Agent/LLM Experience: Experience building with LLMs or agent frameworks - tool and skill design, evaluation, or getting a model to behave reliably against real systems Stack Familiarity: Experience with Django, FastAPI, SQLAlchemy, React, TypeScript, PostgreSQL, Docker, or AWS Compensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $111,000 - $140,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: 401(k) plan with employer matching for contributions Excellent medical, dental, and vision coverage as well as mental health and well-being support Open, flexible vacation policy Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc) Quarterly budget for books and online courses for self-development New hire stipend for home office setup Monthly cell phone & internet stipend Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams-grounded in a wide range of expertise and life experiences-and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process. Please be aware of recruitment scams: we never request payments, all recruitment communications are , and if in doubt, contact us at . About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit .
About BlueLabs BlueLabs is a leading provider of analytics services and technology dedicated to helping our partners do the most good with their data. Our team of analysts, scientists, engineers, and strategists hail from diverse backgrounds yet share a passion for using data to solve the world's greatest social and analytical challenges. Since our inception we've worked with more than 400 organizations ranging from advocacy groups, unions, political campaigns, and international groups. In addition, we service an ever-expanding portfolio of commercial clients in the automotive, travel, CPG, entertainment, healthcare, media, and telecom industries. Along the way, we've developed some of the most innovative tools available in analytics, media optimization, reporting, and influencer outreach. About the team The Strategic Analytics Team at BlueLabs drives high quality, innovative research and analysis across BlueLabs' client sectors, including commercial, political, and non-profit clients, to inform data-driven decisions and strategy. Team members analyze and interpret data, provide strategic program insight, drive innovation across sectors, and collaborate closely with both our client and technical teams. Our team is often called to answer questions like: What are the meaningful messaging takeaways from a survey of industry elites for a major corporation to consider in their paid communication? What political trends should a campaign be aware of, and what are the different pathways to victory? How do we present our models, calculators, and reports, so our partners get the information they need? About the role: As part of the Insights at BlueLabs, you'll be working with a group of analysts and data scientists who work across BlueLabs' client sectors, including commercial, political, and non-profit clients, to inform data-driven decisions and strategy. This position requires a mix of analysis and data management as well as client presentation and communication. You'll be responsible for hard analysis as well as putting together the data infrastructure, reports, and calculators that will power our solutions as well as creating the client-facing materials that summarize those findings. Analysts at BlueLabs are the ones with the best understanding of the nuances of a client's data and our solutions. They can execute on the perfect solution but can also discover the answer that gets us 95% of the way there is a quicker and more efficient way. Some of our work is templated, but our team excels when they come up with creative solutions to the problems. This will require creating new calculators or analyzing existing outputs in a new light. Some examples of projects you might work on: Analyze polling data to discover trends and insights and then create a report that clearly communicates your findings Build crosstabs that detail the makeup of an advertising audience, target universe, or group of survey respondents Present your findings to clients and other stakeholders who may be made up of non-technical and/or highly technical people. Mentor analysts or fellows and support their growth and development Such other reasonable tasks may be assigned by management. Tools of the Trade We work closely with our data science team, so you'll need an understanding of statistical concepts, be able to interpret results and explain them to non-analysts We use big data sets so you will need to be comfortable with tools to access information and analyze that information such as SQL and some statistical and/or spreadsheet software We use an array of business intelligence tools to visualize our findings. Members of our team have different strengths such as GIS or Tableau so we look for some experience using such tools We're only successful if we can communicate our findings; writing skills, PowerPoint, Keynote and other tools of the consultant toolbox will help you succeed in this job What we are seeking: You likely have at least a bachelor's degree in a related field with a statistical background or at least 2+ years of experience analyzing data and building reports You are passionate about harnessing data-driven solutions to improve social outcomes You're eager to learn techniques in data management, analysis, and visualization You can recognize patterns and are careful to check assumptions whether they are your own or someone else's You have excellent attention to detail and a keen eye for design Your experience manipulating data to identify clear insights allows you to be able to conduct data analysis even on tight deadlines, where the problem is unstructured, or the guidance is open ended You've created reports and worked with data visualization and business intelligence tools You've created maps with GIS data and used software such as QGIS or ArcGIS You have experience with programming languages such as Python and SQL You have worked with spreadsheet and presentation software (Excel, Google Sheets, PowerPoint, Keynote) What Recruitment Looks Like: The successful candidate will complete up to three interviews (HR phone call, team member interview, and panel interview). There will also be a technical assessment. During the interview process, you will be asked questions to describe your background and experience relevant to the position. This may include providing examples of projects you worked on, tools or applications you've used, and knowledge you have applied. We often look for explanations of "how or why" so it's helpful to have details ready. What We Offer: BlueLabs offers a friendly work environment and competitive compensation and benefits package including: Salary: $85,000 Premier health, dental, and vision insurance plans 401K matching Unlimited paid time off Paid personal and volunteer leave 13 paid holidays 15 weeks paid parental leave Professional development stipend & tuition reimbursement Macbook Pro laptop & tech accessories Bring Your Own Device (BYOD) stipend for mobile device Employee Assistance Program (EAP) Supportive & collaborative culture Flexible working hours Remote friendly (within the U.S.) Pre-tax transportation options for commuting to our office in Washington, DC Lunches and snacks And more! The salary range for candidates who meet the minimum posted qualifications reflects the Company's good faith understanding and belief as to the wage range, and is accurate as of the date of this job posting. At BlueLabs, we celebrate, support and thrive on differences. Not only do they benefit our services, products, and community, but most importantly, they are to the benefit of our team. Qualified people of all races, ethnicities, ages, sex, genders, sexual orientations, national origins, gender identities, marital status, religions, veterans statuses, disabilities and any other protected classes are strongly encouraged to apply. BlueLabs endeavors to make reasonable accommodations for qualified applicants with a disability unless the accommodation would impose an undue hardship on the operation of our business. If an applicant believes they require such assistance to complete the application or to participate in an interview, or has any questions or concerns, they should contact the Senior Director, People Operations. BlueLabs participates in E-verify. Collection of Personal Information Notice: As you are likely aware, by submitting your job application, you are submitting personal information to our company. We collect various categories of personal information, including identifiers, protected classifications, professional or employment related information and sensitive personal information. We may retain and use this information for up to three years, in order to come to a decision on whether or not you are a good fit for our company. We may also retain or use some of this information to comply with any requirements under law, or for purposes of defending ourselves in any litigation. We do not use this information for any other purpose, or share it with third parties, unless you become an employee. To learn more, or to see our full Notice to Job Applicants, please click here.
09/24/2026
Full time
About BlueLabs BlueLabs is a leading provider of analytics services and technology dedicated to helping our partners do the most good with their data. Our team of analysts, scientists, engineers, and strategists hail from diverse backgrounds yet share a passion for using data to solve the world's greatest social and analytical challenges. Since our inception we've worked with more than 400 organizations ranging from advocacy groups, unions, political campaigns, and international groups. In addition, we service an ever-expanding portfolio of commercial clients in the automotive, travel, CPG, entertainment, healthcare, media, and telecom industries. Along the way, we've developed some of the most innovative tools available in analytics, media optimization, reporting, and influencer outreach. About the team The Strategic Analytics Team at BlueLabs drives high quality, innovative research and analysis across BlueLabs' client sectors, including commercial, political, and non-profit clients, to inform data-driven decisions and strategy. Team members analyze and interpret data, provide strategic program insight, drive innovation across sectors, and collaborate closely with both our client and technical teams. Our team is often called to answer questions like: What are the meaningful messaging takeaways from a survey of industry elites for a major corporation to consider in their paid communication? What political trends should a campaign be aware of, and what are the different pathways to victory? How do we present our models, calculators, and reports, so our partners get the information they need? About the role: As part of the Insights at BlueLabs, you'll be working with a group of analysts and data scientists who work across BlueLabs' client sectors, including commercial, political, and non-profit clients, to inform data-driven decisions and strategy. This position requires a mix of analysis and data management as well as client presentation and communication. You'll be responsible for hard analysis as well as putting together the data infrastructure, reports, and calculators that will power our solutions as well as creating the client-facing materials that summarize those findings. Analysts at BlueLabs are the ones with the best understanding of the nuances of a client's data and our solutions. They can execute on the perfect solution but can also discover the answer that gets us 95% of the way there is a quicker and more efficient way. Some of our work is templated, but our team excels when they come up with creative solutions to the problems. This will require creating new calculators or analyzing existing outputs in a new light. Some examples of projects you might work on: Analyze polling data to discover trends and insights and then create a report that clearly communicates your findings Build crosstabs that detail the makeup of an advertising audience, target universe, or group of survey respondents Present your findings to clients and other stakeholders who may be made up of non-technical and/or highly technical people. Mentor analysts or fellows and support their growth and development Such other reasonable tasks may be assigned by management. Tools of the Trade We work closely with our data science team, so you'll need an understanding of statistical concepts, be able to interpret results and explain them to non-analysts We use big data sets so you will need to be comfortable with tools to access information and analyze that information such as SQL and some statistical and/or spreadsheet software We use an array of business intelligence tools to visualize our findings. Members of our team have different strengths such as GIS or Tableau so we look for some experience using such tools We're only successful if we can communicate our findings; writing skills, PowerPoint, Keynote and other tools of the consultant toolbox will help you succeed in this job What we are seeking: You likely have at least a bachelor's degree in a related field with a statistical background or at least 2+ years of experience analyzing data and building reports You are passionate about harnessing data-driven solutions to improve social outcomes You're eager to learn techniques in data management, analysis, and visualization You can recognize patterns and are careful to check assumptions whether they are your own or someone else's You have excellent attention to detail and a keen eye for design Your experience manipulating data to identify clear insights allows you to be able to conduct data analysis even on tight deadlines, where the problem is unstructured, or the guidance is open ended You've created reports and worked with data visualization and business intelligence tools You've created maps with GIS data and used software such as QGIS or ArcGIS You have experience with programming languages such as Python and SQL You have worked with spreadsheet and presentation software (Excel, Google Sheets, PowerPoint, Keynote) What Recruitment Looks Like: The successful candidate will complete up to three interviews (HR phone call, team member interview, and panel interview). There will also be a technical assessment. During the interview process, you will be asked questions to describe your background and experience relevant to the position. This may include providing examples of projects you worked on, tools or applications you've used, and knowledge you have applied. We often look for explanations of "how or why" so it's helpful to have details ready. What We Offer: BlueLabs offers a friendly work environment and competitive compensation and benefits package including: Salary: $85,000 Premier health, dental, and vision insurance plans 401K matching Unlimited paid time off Paid personal and volunteer leave 13 paid holidays 15 weeks paid parental leave Professional development stipend & tuition reimbursement Macbook Pro laptop & tech accessories Bring Your Own Device (BYOD) stipend for mobile device Employee Assistance Program (EAP) Supportive & collaborative culture Flexible working hours Remote friendly (within the U.S.) Pre-tax transportation options for commuting to our office in Washington, DC Lunches and snacks And more! The salary range for candidates who meet the minimum posted qualifications reflects the Company's good faith understanding and belief as to the wage range, and is accurate as of the date of this job posting. At BlueLabs, we celebrate, support and thrive on differences. Not only do they benefit our services, products, and community, but most importantly, they are to the benefit of our team. Qualified people of all races, ethnicities, ages, sex, genders, sexual orientations, national origins, gender identities, marital status, religions, veterans statuses, disabilities and any other protected classes are strongly encouraged to apply. BlueLabs endeavors to make reasonable accommodations for qualified applicants with a disability unless the accommodation would impose an undue hardship on the operation of our business. If an applicant believes they require such assistance to complete the application or to participate in an interview, or has any questions or concerns, they should contact the Senior Director, People Operations. BlueLabs participates in E-verify. Collection of Personal Information Notice: As you are likely aware, by submitting your job application, you are submitting personal information to our company. We collect various categories of personal information, including identifiers, protected classifications, professional or employment related information and sensitive personal information. We may retain and use this information for up to three years, in order to come to a decision on whether or not you are a good fit for our company. We may also retain or use some of this information to comply with any requirements under law, or for purposes of defending ourselves in any litigation. We do not use this information for any other purpose, or share it with third parties, unless you become an employee. To learn more, or to see our full Notice to Job Applicants, please click here.
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. 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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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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
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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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
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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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 RO Performance Team is accountable for the largest metrics system deployment in the AV industry. The team manages data pipelines that monitor Waymo's AV fleet in the real world at various latencies: from minutes to hours; supporting critical business decisions for deployments in new markets and identifying emergent business critical challenges. In addition, the same pipeline technologies are deployed for the virtual world to measure key outcomes from Waymo's massive scale simulations, generating insights to support new Driver releases. Important objectives for the next couple of years include: Reliably scaling as the business scales, Waymo is in its fast expansion phase and systems have to be built to support 100x growth. Timeliness: As Waymo's deployments accelerate across the globe, time to first detection needs to consistently improve. Comprehensive coverage: Expanding into new weather conditions and new markets brings new challenges. Increasing the metric and detection offerings to meet these challenges is key to achieving our business goals. The team works closely with many other teams such as: metrics development teams including large AI deployments, System engineers and Data scientists that produce definitions and quality controls, infrastructure and UI teams that support underlying capabilities, product teams to stay sensitive to changing business needs, and site reliability engineering (SRE) teams to maintain high system uptime. You Will: Be a part of the Event Insights sub-team, Once metric events, e.g., a hard brake occurred, are minted from heavy logs processing pipelines, an event lifecycle emerges where such events may get sent to other systems for further refinement, including but not limited to: human triage, VLM inference, clustering. Key workstreams that the TLM will be accountable for include: Clustering: Work on creation of a dynamic event clustering product to produce event clusters at low latency for rapid understanding of emerging issues during new deployments of the Waymo Driver in simulation or in the real world. Storage & APIs: Events need to be stored and queried by different downstream systems. Consumption APIs include pull or push based paradigms. Labels received from human triage or VLMs update existing events. Low Latency Orchestration: Gathering further event insights requires interaction with other systems at Waymo such as for human triage or large VLM inference. Orchestrating these interactions reliably and at low latency is key for meeting Waymo's challenges. Visualization: Work closely with partner UI teams to ensure that event insights can be delivered to end consumers and provide value for understanding the Waymo Driver's performance. You have: 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience C++ proficiency Python familiarity SQL familiarity Excited about autonomous driving, Simulation + Eval We prefer: 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system. B.Sc. in Computer Science Experience working with large FAANG scale distributed 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
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
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
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
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
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning. Use simulation creatively and mine real world driving logs to measure driving performance. Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes. Champion code health and best practices in a large and complex code base. Analyze data and make recommendations on how to improve metric quality and interpretability. Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions. You have: BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area Strong self-motivation to navigate complex systems and pursue open-ended problems to completion 2-3 years of industry experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL Performing statistical analyses Building data processing pipelines Writing, reviewing, and merging code following industry standards for code health and maintainability Quant/data fluency is a top requirement We prefer: Experience coding in C++ Experience with ML Experience with A/B experiment infrastructure Experience building and validating metrics to measure quality in complex systems Exposure to ad-hoc data analysis tools for rapid modeling and prototyping Experience working in the AV industry The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions. To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundation models trained on our datasets and diffusion technology. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple scenarios to rigorously test our autonomous driving systems. In this hybrid role, you will report to a Senior Engineering Manager You will: Be part of a world-class applied ML team dedicated to advancing ultra-realistic autonomous vehicle (AV) simulations by leveraging Generative AI technologies. Apply deep domain expertise in ML, especially GenAI, to push the boundaries of simulation realism and autonomous driving capabilities. Independently manage the entire lifecycle of product innovations, from prototyping to productization, scaling simulations and data processing systems. Work within a collaborative applied ML engineering team that transforms research ideas into production-ready solutions. You have: 7+ years experience in applied Deep Learning 7+ years coding and design skills 7+ years of experience solving complex production problems using state-of-the-art ML techniques 7+ years of experience taking research to production Expertise in Data Analysis or Data Science We prefer: PhD degree in Computer Science or a similar discipline Direct experience in Generative AI, including multi-modal foundation models and Diffusion models. 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 and training the Waymo Driver. Our team is a diverse and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions. To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundation models trained on our datasets and diffusion technology. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple scenarios to rigorously test our autonomous driving systems. In this hybrid role, you will report to a Senior Engineering Manager You will: Be part of a world-class applied ML team dedicated to advancing ultra-realistic autonomous vehicle (AV) simulations by leveraging Generative AI technologies. Apply deep domain expertise in ML, especially GenAI, to push the boundaries of simulation realism and autonomous driving capabilities. Independently manage the entire lifecycle of product innovations, from prototyping to productization, scaling simulations and data processing systems. Work within a collaborative applied ML engineering team that transforms research ideas into production-ready solutions. You have: 7+ years experience in applied Deep Learning 7+ years coding and design skills 7+ years of experience solving complex production problems using state-of-the-art ML techniques 7+ years of experience taking research to production Expertise in Data Analysis or Data Science We prefer: PhD degree in Computer Science or a similar discipline Direct experience in Generative AI, including multi-modal foundation models and Diffusion models. 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
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech
09/23/2026
Full time
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech
09/23/2026
Full time
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech
09/23/2026
Full time
Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. We are seeking a Scientific AI Engineer to design and build end-to-end AI solutions that directly impact Oncology R&D decision-making. This role sits at the intersection of deep scientific understanding and hands on AI engineering, translating complex biological, translational, and clinical questions into applied AI solutions. In this role, you will partner closely with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI enabled insights, with a strong emphasis on speed, scientific rigor, and real-world usability. Key Responsibilities Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges. Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature). Own solutions end-to-end, from problem framing and data exploration through model development and user facing outputs. Collaborate closely with domain experts to ensure solutions are scientifically grounded and decision relevant. Rapidly iterate on prototypes based on user feedback and evolving scientific needs. Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead. Document methods, assumptions, and limitations to support transparency and responsible AI practices. Basic Qualifications Bachelor's degree and 6+ years of relevant work experience OR Master's degree and 5+ years of experience OR PhD and 1+ years of experience. Advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred. Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments. Strong hands-on programming skills (e.g., Python) and experience working with data pipelines and ML frameworks. Solid understanding of Oncology biology, translational science, or clinical development workflows. Ability to operate independently in ambiguous problem spaces and deliver working prototypes. Preferred Qualifications Experience in pharma, biotech, or AI driven health technology startups. Familiarity with prototyping approaches for AI products rather than long cycle production systems. Experience working with large, heterogeneous datasets common to Oncology R&D. The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits (). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. Information & Business Tech