Machine Learning Infrastructure Engineer

Peloton, a leading fitness technology company, is seeking a Machine Learning Infrastructure Engineer to join their AI/ML organization. This role focuses on building and scaling ML infrastructure for computer vision and recommender systems in the fitness domain. The position offers an unique opportunity to work with cutting-edge ML technologies while supporting Peloton's mission of providing exceptional fitness experiences.

The role involves close collaboration with ML Engineers, Data Engineers, and Data Scientists to develop robust infrastructure supporting model development, deployment pipelines, and experimentation at scale. You'll be responsible for creating the essential infrastructure that connects data systems with ML operations, ensuring efficient model lifecycle management and monitoring.

As a Machine Learning Infrastructure Engineer at Peloton, you'll work in a hybrid environment (3 days in office) with competitive compensation ($176,748—$229,772) and comprehensive benefits. The company offers extensive professional development opportunities, equity participation, and the chance to impact millions of members' fitness journeys.

The ideal candidate should have strong experience in ML infrastructure development, Python programming, and familiarity with cloud services and ML tools. This role presents an exceptional opportunity to shape the future of connected fitness through advanced ML systems while working with a talented team in a supportive, innovative environment.