Peloton is looking to drive personalization and recommendations for their highly engaged members across multiple platforms.
Requirements
- 2+ years of experience working in at least one of following ML subject areas: 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.
- Comfortable working with near real-time ML applications.
- Consistent track record of working with product managers to launch ML-based product features.
Responsibilities
- Build and improve ML pipelines that power Peloton’s content recommendations.
- Research and apply outstanding 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.
Other
- Degree in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
- MS/PhD in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
- Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
