Lead Machine Learning Engineer, Shopping - Feed (Remote)

Capital One is seeking a Lead Machine Learning Engineer to join their Shopping Feed team in a remote capacity. This role presents an exciting opportunity to work in a dynamic, remote-first engineering environment focused on greenfield problem-solving. As part of a growth-stage business unit with a startup mindset, you'll be instrumental in building technology that helps customers save money.

The position requires expertise in productionizing machine learning applications and systems at scale. You'll be working within a fast-moving, highly collaborative Agile team, where you'll drive technical designs, development, and implementation of ML applications. Leadership in machine learning architectural design is crucial, as you'll be developing and reviewing model and application code while ensuring high availability and performance of ML applications.

Your responsibilities will span multiple disciplines, including ML Engineering, Operations, Modeling, and Data Engineering. You'll work with technologies such as Docker, Nomad, SQL, Python, PyTorch, and Transformers. The role involves collaborating with Product and Data Science teams to solve real-world business problems, building optimized data pipelines, and ensuring proper model governance and risk management.

The ideal candidate should have strong experience in distributed computing, programming skills in Python, Scala, or Java, and a proven track record in building and scaling ML systems. You'll be expected to mentor junior developers and serve as a technical bridge between product partners. The position offers competitive compensation ranging from $175,800 to $200,700, along with comprehensive benefits and performance-based incentives.

This role represents more than just a job – it's an opportunity to be part of a collaborative and forward-thinking community where your contributions will significantly impact the future of financial technology. Join Capital One as we continue to push boundaries and redefine the future of our industry through innovative machine learning solutions.