YOUR DAILY IMPACT AT PELOTON

• Build and improve ML pipelines that power Peloton’s content recommendations.
• Research and apply best-in-class machine learning techniques for recommender systems.
• Evaluate, implement, and improve machine learning models.
• Run A/B tests and experiments and analyze the results in collaboration with our product analysts.
• Productionize, deploy and monitor machine learning models and services.
• Collaborate and work closely with our platform teams to leverage their tools and infrastructure to rapidly iterate on ideas that drive delightful personalized experiences for millions of users.

PREFERRED QUALIFICATIONS

• MS/PhD in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
• Comfortable working with near real-time ML applications.
• Proven track record of working with product managers to launch ML-based product features.
  

  LI-RF2

LI-Hybrid

The Personalization team at Peloton is looking for a machine learning engineer to drive personalization and recommendations for our highly engaged members across multiple platforms. Their main focus will be to optimize the engagement and discovery of Peloton content through research and application of AI and ML techniques for content recommendations. They will work closely with ML Engineers, Software Engineers, Product Managers and Product Analysts to test ideas that drive member engagement. They will have a unique opportunity to work with one of the most granular data related to member engagement in the fitness industry. We’re looking for someone who’s passionate about fitness and is excited about the challenges of AI and machine learning to define the future of connected fitness.