The Personalization team at Peloton is looking for a machine learning engineer to drive our personalization & recommendations for our highly engaged members across multiple platforms. Their main focus will be to optimize the engagement & discovery of Peloton content through research & application of AI & ML techniques for content recommendations. They will work closely with ML Engineers, Software Engineers, Product Managers & 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. Were looking for someone whos passionate about fitness & is excited about the challenges of AI & machine learning to define the future of connected fitness.
- Build & improve ML pipelines that power Pelotons content recommendations.
- Research & apply best-in-class machine learning techniques for recommender systems.
- Evaluate, implement, & improve machine learning models.
- Run A/B tests & experiments & analyze the results in collaboration with our product analysts.
- Productionize, deploy & monitor machine learning models & services.
- Collaborate & work closely with our platform teams to leverage their tools & infrastructure to rapidly iterate on ideas that drive delightful personalized experiences for millions of users.
- 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 disciplines: recommender systems, natural language processing or computer vision.
- Strong understanding of software engineering principles & fundamentals including data structures & algorithms.
- Experience writing code in Python, Java, Kotlin, Go, C/C++ with documentation for reproducibility.
- Experience with relational & non-relational databases such as Postgres, MySQL, Cassandra, or DynamoDB.
- Experience writing & speaking about technical concepts to business, technical, & lay audiences & 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.
- Proven track record of working with product managers to launch ML-based product features.
Peloton uses technology + design to connect the world through fitness, empowering people to be the best version of themselves anywhere, anytime. We have reinvented the fitness industry by developing a first-of-its-kind subscription platform. Seamlessly combining hardware, software, & streaming technology, we create digital fitness & wellness content & products that Members love. In 2020 Peloton committed to becoming an antiracist organization with the launch of the Peloton Pledge. Learn more, here.
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. In order to be the best version of Peloton, we are deeply committed to building a diverse workforce & inclusive culture where all of our team members can be the best version of themselves. This work has no endpoint; it is the constant work of running an organization that strives to reach its full potential. As a first step in our commitment, we announced the Peloton Pledge to invest $100 million over the next four years to fight racial injustice & inequity in our world, & to promote health & wellbeing for all, from the inside out.