Description
The Personalization team at Peloton is looking for a Machine Learning Engineer to drive personalization and recommendations for highly engaged members across multiple platforms.
Your main focus will be to optimize the engagement and discovery of Peloton content through research and application of AI and ML techniques for content and non-content recommendations.
You will own the end-to-end lifecycle of our ML products, from data engineering and foundational infrastructure to building scalable microservices and LLM-based solutions that serve our users in real-time.
Responsibilities:
- Build and improve AI and ML pipelines that power Peloton's 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 product analysts
- Engineer, deploy, and monitor scalable microservices that serve high-concurrency machine learning inference endpoints
- Develop and scale evaluation pipelines to measure model performance and bias in production environments
- Design, implement, and maintain robust microservices to host high-throughput ML inference endpoints
- Architect and manage the ML infrastructure necessary to support sophisticated LLM-based features and real-time personalization
Requirements:
- Degree in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
- 3+ years of experience working in at least one of the following ML disciplines: 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
- Experience designing and deploying scalable, low-latency microservices for ML model serving
- Hands-on experience with modern MLOps, including automated evaluation pipelines and model monitoring
Benefits:
- 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 more