Lead Machine Learning Engineer (Manager IC)

Capital One is seeking a Lead Machine Learning Engineer (Manager IC) to join its Risk Tech organization in McLean, VA, onsite. This senior individual-contributor management role centers on designing, deploying, and supporting AI-powered software and ML systems, collaborating with cross-functional teams to shape Capital One's AI roadmap and deliver tangible value for associates and customers.

Responsibilities

• Collaborate with a cross-disciplinary team of engineers, data scientists, product managers, and designers to deliver AI-driven products that transform how associates work and create value for customers.
• Design and implement AI software components that utilize machine learning models, covering evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
• Fine-tune and evaluate machine learning and foundation models.
• Work within an Agile, cross-functional team to build and improve software that leverages state-of-the-art AI and ML capabilities.
• Provide strategic technical leadership to shape the long-term Capital One AI systems roadmap.
• Leverage a broad mix of open-source and SaaS AI technologies.
• Inform ML infrastructure decisions based on modeling techniques and related challenges.
• Retrain, maintain, and monitor models in production.
• Construct optimized data pipelines to feed ML models.
• Ensure code quality, model governance, and adherence to Responsible and Explainable AI practices to manage risk and reduce vulnerabilities.

Requirements

• Bachelor’s Degree
• Minimum six years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• At least four years of experience programming with Python, Scala, or Java
• At least two 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

• Enjoys building robust systems and takes pride in high-quality work while aiming to advance banking practices in a responsible way.
• Excellent communicator who can explain complex technical concepts to non-technical partners, including presenting to large audiences when needed.
• Stays current with AI research and can interpret scientific publications to apply novel techniques in production thoughtfully.
• Adapts quickly to undefined problems, asks questions, and identifies root causes, articulating findings clearly; ready to propose new ideas even if unproven.
• Deep technical foundation in engineering and mathematics, with the ability to recognize and exploit optimization opportunities across hardware, software, and AI.
• Resilient and forward-thinking, capable of forging paths to achieve business goals in uncertain environments.
• Committed to staying informed about the latest AI systems and applying innovative techniques in production judiciously.

Strategic & Business-Oriented

Beyond technology, you understand business needs and how AI can address them. You prioritize work and develop strategies that maximize business value and measurable impact.

Highly Collaborative & Transparent

You collaborate across engineering, product, and data science teams, articulating progress, blockers, and decisions clearly. You share knowledge, align stakeholders, and support the success of the entire team.

Technically Mature & Humble

You bring a strong engineering and mathematical foundation, approach problems with calm maturity, and communicate findings concisely. You make and stand by team decisions.

Flexible & Fungible

You are willing to contribute wherever needed, comfortable across different parts of the technology stack, and adapt to shifting priorities.

A Lifelong Learner

You enjoy staying current with AI research and apply novel techniques to production when they offer clear business value, maintaining focus on impact and practicality.