Lead Machine Learning Engineer

Capital One is seeking a Lead Machine Learning Engineer to support horizontal AI enablement efforts across Finance technology. This onsite role in New York focuses on turning AI capabilities into practical, end user facing use cases for Finance lines of business, while establishing reusable engineering standards for model evaluation, deployment, and operations.

Working with a cross-functional group of engineers, data scientists, product managers, and designers, you will lead ML engineering activities spanning model experimentation, large language model inference, similarity search, guardrails, governance, observability, agentic AI, and production monitoring for deployed models.

What you’ll do

• Partner with cross-functional teams to deliver AI-powered products that support how associates work and provide value for customers.
• Design, develop, test, deploy, and support AI software components, including model evaluation and experimentation, LLM inference, similarity search, guardrails, governance, observability, and agentic AI.
• Fine-tune, develop, and evaluate machine learning and foundation models.
• Collaborate in an Agile environment to create and enhance software that applies state-of-the-art AI and ML capabilities.
• Contribute thought leadership and technical direction for a long term roadmap for pioneering AI systems.
• Use a broad stack of Open Source and SaaS AI technologies.
• Apply your understanding of ML modeling techniques and issues to inform ML infrastructure decisions.
• Retrain, maintain, and monitor production models.
• Construct optimized data pipelines to feed ML models.
• Manage code to reduce vulnerabilities, ensure strong governance from a risk perspective, and follow best practices for Responsible and Explainable AI.

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

Preferred qualifications

• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 7+ years of experience designing, developing, delivering, and supporting AI services at scale
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing AI and ML algorithms or technologies using Python
• 2+ years of experience with Retrieval Augmented Generation (RAG)
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion
• Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure

Technology stack

• Python, Scala, Java
• scikit-learn, PyTorch
• Dask, Spark, TensorFlow
• Retrieval Augmented Generation (RAG)
• AWS Bedrock, Google Cloud, Azure
• Open Source, SaaS
• Large language model inference

Compensation and benefits

Salary range: USD 215,200 - 245,600 per year. Capital One also offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being, along with performance-based incentive compensation that may include cash bonus(es) and/or long term incentives (LTI).