Lead Machine Learning Engineer

Join Capital One in an onsite role in New York, NY, leading finance technology AI enablement work across horizontal teams. You will help build and operate AI capabilities that associates can use day to day, while contributing to long-term technical direction for responsible and explainable AI systems. Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being, plus performance-based incentive compensation that may include cash bonus(es) and/or long term incentives (LTI). Salary range: USD 215,200 - 245,600 per year.

Responsibilities

• Partner with engineers, data scientists, product managers, and designers to deliver AI-powered products that change how associates work and provide value to customers.
• Design, develop, test, deploy, and support AI software components that use 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.
• Collaborate in a cross-functional Agile team to create and enhance software that uses state-of-the-art AI and ML capabilities.
• Provide thought leadership and technical vision to help shape the long-term roadmap for pioneering AI systems at Capital One.
• Leverage a broad stack of Open Source and SaaS AI technologies.
• Use expertise in ML modeling techniques and issues to inform ML infrastructure decisions.
• Retrain, maintain, and monitor models in production.
• Construct optimized data pipelines that feed ML models.
• Manage code to reduce vulnerabilities, ensure models are governed from a risk perspective, and follow best practices for Responsible and Explainable AI.

Requirements

• Bachelor’s Degree
• 6+ years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• 4+ years of experience programming with Python, Scala, or Java
• 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
• Open Source, SaaS, large language model inference

Preferred Qualifications

• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or similar field
• 7+ years designing, developing, delivering, and supporting AI services at scale
• 3+ years building production-ready data pipelines that feed ML models
• 3+ years on-the-job experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
• 3+ years 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 people leader experience
• 1+ years 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, or Azure