Machine Learning Engineer

ABOUT THE ROLE The Personalization team at Peloton is looking for a machine learning engineer to drive our 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. 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 use their tools and infrastructure to rapidly iterate on ideas that drive delightful personalized experiences for millions of users. YOU BRING TO PELOTON M.S. in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc. 2+ years of industrial experience in at least one of ML fields: recommender systems, natural language processing or computer vision. Strong understanding of software engineering principles and fundamentals including data structures and algorithms. Experience writing code in Python, Java, Kotlin, Go, C/C++ with documentation for reproducibility. Experience with relational and non-relational databases such as Postgres, MySQL, Cassandra, or DynamoDB. Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations. PhD in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc. Comfortable working with near real-time ML applications. Consistent track record of working with product managers to launch ML-based product features. COMPENSATION AND BENEFITS The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including individual performance, business objectives, and if the location for the job changes. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits. As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including: Medical, dental and vision insurance Generous paid time off policy Short-term and long-term disability Access to mental health services 401k, tuition reimbursement and student loan paydown plans Employee Stock Purchase Plan Fertility and adoption support and up to 18 weeks of paid parental leave Child care and family care discounts Free access to Peloton Digital App and apparel and product discounts Commuter benefits and Citi Bike Discount Pet insurance and so much more! ABOUT PELOTON: Peloton (NASDAQ: PTON), provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together immersive classes, cutting-edge technology and hardware, and the Peloton App with multiple tiers to personalize the Peloton experience [with or without equipment]. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com. At Peloton, we motivate the world to live better. “Together We Go Far” means that we are greater than the sum of our parts, stronger collectively when each one of us is at our best.

#J-18808-Ljbffr