Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences)

About the role

The role of a Senior Lead Machine Learning Engineer at Capital One involves leading the development and delivery of AI-powered products and components that solve real-world business problems. This includes designing, building, and delivering AI services at scale, collaborating with cross-functional teams, and ensuring high availability and performance of machine learning applications.

Responsibilities

• Lead dedicated pods of software, data, and machine learning engineers in building AI/ML capabilities for Credit and Financial Risk Management products.
• Design, build, and deliver AI-powered products and components that solve real-world business problems, leveraging expertise in model experimentation, LLM inference, similarity search, and agentic AI.
• Collaborate with a cross-functional team of engineers, data scientists, and designers to develop and scale AI-powered products that enable optimized associate performance and deliver world-class customer value.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Leverage a broad stack of Open Source and SaaS AI technologies and use programming languages like Python, Scala, or Java.

Requirements

• Bachelor’s Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing
• At least 4 years of experience programming with Python, Scala, or Java
• At least 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications

• Master's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a similar field
• 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 staying abreast of latest ML research with an intuitive ability to understand scientific publications and judiciously apply novel techniques in production
• 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

Benefits

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.

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning 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.

Schedule

This role is full-time.

Qualifications

• Category: Engineering
• Experience Level: Sr. Manager
• Primary Address: McLean, Virginia

Skills

• Programming Languages: Python, Scala, Java
• Technologies: Distributed Computing, Retrieval Augmented Generation (RAG)
• Cloud Platforms: AWS Bedrock, Google Cloud, Azure
• Data Pipelines: Complex Data Pipelines
• Machine Learning Techniques: Model Experimentation, LLM Inference, Similarity Search, Agentic AI
• Software Development: Continuous Integration, Continuous Deployment
• Security: Vulnerability Management, Risk Governance, Responsible and Explainable AI