Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences)

Senior Lead Machine Learning Engineer role at Capital One, based onsite in McLean, VA, focused on productionizing ML applications at scale and shaping ML architecture, development, and deployment.

Responsibilities

• Lead dedicated cross-disciplinary pods of software, data, and ML engineers to build AI and ML capabilities for Credit and Financial Risk Management products, serving as a technical mentor on core technologies
• Design, build, and deliver AI powered products and components that address real world business problems, applying model experimentation, LLM inference, similarity search, and agentic AI within a collaborative Product and Data Science environment
• Partner with engineers, data scientists, and designers to develop and scale AI powered products that improve associate performance and deliver world class customer value
• Guide ML infrastructure decisions based on modeling techniques, including model choice, data and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Address complex problems by writing and testing application code, building and validating ML models, and automating tests and deployment
• Retrain, monitor, and maintain models in production
• Utilize or build cloud based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
• Maintain code quality to reduce vulnerabilities, ensure model governance from a risk perspective, and adhere to Responsible and Explainable AI practices
• 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 (Internship experience does not apply)
• 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

Technologies

• Python
• Scala
• Java
• AWS Bedrock
• Google Cloud
• Azure

Benefits

• Health benefits
• Financial benefits
• Incentives (performance-based incentive compensation, including cash bonuses and/or long-term incentives)
• Other benefits