Lead Machine Learning Engineer (Manager IC)

Capital One seeks a Lead Machine Learning Engineer (Manager IC) to sit onsite in McLean, VA. This role designs, deploys, and sustains AI powered software and ML systems across Risk Tech, collaborating with cross-functional teams and shaping the long-term AI roadmap.

Responsibilities

• Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI powered products that transform associates' workflows and deliver value to customers.
• Design, develop, test, deploy, and support AI software components using 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.
• Work as part of an Agile, cross-functional team to create software that leverages 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 ML infrastructure decisions with an understanding of ML modeling techniques and related challenges.
• Retrain, maintain, and monitor models in production.
• Construct optimized data pipelines to feed ML models.
• Ensure code quality minimizes vulnerabilities, maintains model governance, and aligns with Responsible and Explainable AI practices.

Requirements

• 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, Scala, or Java.
• At least 2 years of experience building, scaling, and optimizing ML systems.

Technologies

• Python
• Scala
• Java
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow
• Retrieval Augmented Generation (RAG)
• AWS Bedrock
• Google Cloud
• Azure

Benefits

• Performance-based incentive compensation (cash bonus and/or long term incentives)
• Health benefits
• Financial benefits

The Ideal Candidate

• You enjoy building robust systems, take pride in quality, and are motivated to do the right thing while solving banking challenges.
• You communicate clearly, translating complex technical concepts to non-technical partners across the business, including presentations to larger audiences.
• You stay current with AI research and can translate publications into production-ready approaches.
• You adapt quickly, bring clarity to ambiguous problems, ask insightful questions, and share new ideas with confidence.
• You have a solid engineering and mathematical foundation, and you leverage expertise across hardware, software, and AI to spot optimization opportunities.
• You are a resilient trailblazer who can chart new paths to achieve business goals when the route is not obvious.
• You maintain a passion for AI research and systems, applying novel approaches judiciously in production.
• Strategic and business oriented: think beyond technology, deeply understand business needs and how AI can solve them; you strategize and prioritize work to deliver maximum business value.
• Highly collaborative and transparent: partner across engineering, product, and data science; communicate progress and blockers openly; share knowledge for the team's success.
• Technically mature and humble: strong engineering and math foundation; resilient problem solver; articulate findings succinctly; commit to team decisions.
• Flexible and fungible: willing to contribute across the tech stack and adapt to shifting priorities.
• A lifelong learner: stay current with AI research and apply novel techniques judiciously with focus on business impact.