Capital One
Lead Machine Learning Engineer – ML/AI
At Capital One, we are changing banking for good by creating responsible and reliable AI‑powered systems. Our AI & ML solutions bring simplicity to banking, and we are building a world‑class applied science team to deliver breakthrough product experiences and scalable high‑performance AI infrastructure. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. In this role you will work with our internal Audit team and partners across the company to build and deploy proprietary solutions powered by state‑of‑the‑art AI technology.
You will:
Partner with a cross‑functional team of engineers, data scientists, product managers, and designers to deliver AI‑powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
Fine‑tune, develop and evaluate machine learning and foundation models.
Collaborate as part of a cross‑functional Agile team to create and enhance software that utilizes state‑of‑the‑art AI and ML capabilities.
Contribute thought leadership and technical vision to the long‑term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of Open Source and SaaS AI technologies.
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
Ensure all code is well‑managed to reduce vulnerabilities, models are well‑governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
The Ideal Candidate:
You love to build systems, take pride in the quality of your work, and share our passion to do the right thing. You want to work on problems that will help change banking for good.
You are a passionate communicator, comfortable with explaining complex technical concepts to non‑technical partners across the business, sometimes in front of large audiences.
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. 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 enable you to see and exploit optimization opportunities that others miss.
You are a resilient trail‑blazer who can forge new paths to achieve business goals when the route is unknown.
Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production.
Strategic & Business‑Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don’t just build; you strategize and prioritize work that delivers the greatest business value.
Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team.
Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem‑solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions.
Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities.
A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact.
Basic Qualifications:
Bachelor’s degree.
At least 6 years of experience designing and building data‑intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Go, Scala, or Java.
At least 3 years of experience deploying scalable software solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
Preferred Qualifications:
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.
6 years of experience designing, developing, delivering, and supporting AI services at scale.
3 years of experience developing AI and ML algorithms or technologies using Python.
2 years of experience with Retrieval Augmented Generation (RAG).
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F‑1 OPT, F‑1 STEM OPT, F‑1 CPT, J‑1, TN, E‑2, E‑3, L‑1 and O‑1, or any EADs or other forms of work authorization that require immigration support from an employer).
Cambridge, MA: $193,400 - $220,700 for Lead Machine Learning Engineer McLean, VA: $193,400 - $220,700 for Lead Machine Learning Engineer New York, NY: $211,000 - $240,800 for Lead Machine Learning Engineer Richmond, VA: $175,800 - $200,700 for Lead Machine Learning Engineer
Benefits: Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
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.
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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com.
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You will:
Partner with a cross‑functional team of engineers, data scientists, product managers, and designers to deliver AI‑powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
Fine‑tune, develop and evaluate machine learning and foundation models.
Collaborate as part of a cross‑functional Agile team to create and enhance software that utilizes state‑of‑the‑art AI and ML capabilities.
Contribute thought leadership and technical vision to the long‑term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of Open Source and SaaS AI technologies.
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
Ensure all code is well‑managed to reduce vulnerabilities, models are well‑governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
The Ideal Candidate:
You love to build systems, take pride in the quality of your work, and share our passion to do the right thing. You want to work on problems that will help change banking for good.
You are a passionate communicator, comfortable with explaining complex technical concepts to non‑technical partners across the business, sometimes in front of large audiences.
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. 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 enable you to see and exploit optimization opportunities that others miss.
You are a resilient trail‑blazer who can forge new paths to achieve business goals when the route is unknown.
Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production.
Strategic & Business‑Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don’t just build; you strategize and prioritize work that delivers the greatest business value.
Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team.
Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem‑solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions.
Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities.
A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact.
Basic Qualifications:
Bachelor’s degree.
At least 6 years of experience designing and building data‑intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Go, Scala, or Java.
At least 3 years of experience deploying scalable software solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
Preferred Qualifications:
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.
6 years of experience designing, developing, delivering, and supporting AI services at scale.
3 years of experience developing AI and ML algorithms or technologies using Python.
2 years of experience with Retrieval Augmented Generation (RAG).
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F‑1 OPT, F‑1 STEM OPT, F‑1 CPT, J‑1, TN, E‑2, E‑3, L‑1 and O‑1, or any EADs or other forms of work authorization that require immigration support from an employer).
Cambridge, MA: $193,400 - $220,700 for Lead Machine Learning Engineer McLean, VA: $193,400 - $220,700 for Lead Machine Learning Engineer New York, NY: $211,000 - $240,800 for Lead Machine Learning Engineer Richmond, VA: $175,800 - $200,700 for Lead Machine Learning Engineer
Benefits: Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
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.
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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com.
#J-18808-Ljbffr