Lead Machine Learning Engineer

Responsibilities

• Partner with cross-functional teams of engineers, data scientists, and product managers to deliver AI-powered risk management products.
• Design, develop, test, and deploy AI software components, including LLM inference, similarity search, and agentic AI.
• Fine-tune, develop, and evaluate machine learning and foundation models.
• Construct optimized data pipelines to feed ML models and maintain models in production.
• Contribute technical vision and thought leadership to the long-term roadmap of pioneering AI systems.
• Ensure all code follows best practices in Responsible and Explainable AI, including governance and observability.

Requirements

• Bachelor's Degree.
• At least 6 years of experience designing and building data-intensive solutions using distributed computing.
• 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 and supporting AI services at scale.
• 3+ years of experience with industry-recognized ML frameworks such as PyTorch, TensorFlow, scikit-learn, Dask, or Spark.
• 2+ years of experience with Retrieval Augmented Generation (RAG).
• Experience deploying scalable AI/ML solutions in public clouds such as AWS Bedrock, Google Cloud, or Azure.
• Experience leading teams or people management.

Benefits

• Comprehensive health, financial, and wellness benefits.
• Performance-based incentive compensation, including potential cash bonuses or long-term incentives.
• A culture focused on diversity, inclusion, and continuous learning.

About the Company

Capital One is changing banking for good by creating responsible and reliable AI-powered systems. We leverage deep expertise in machine learning and state-of-the-art technology to build scalable, high-performance AI infrastructure that brings humanity and simplicity to banking.