Machine Learning Engineer III

The posting, as Peloton wrote it

ABOUT THE ROLE

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. 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. You will work closely with ML Engineers, Software Engineers, Product Managers and Product Analysts to test ideas that drive member engagement. You 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 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 our 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

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

YOU BRING TO PELOTON

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 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 m
[…]
lerate innovation in the work we do for our members. However, in our hiring process, our priority remains in getting to know you and your unique qualifications. To ensure a fair and equitable process, we do not permit the use of AI tools during any stage of the application and interview process. In considering you as an applicant, we want to understand your skills, experiences, and motivations without mediation through an AI system. We also want to directly assess your communication skills without the use of an AI tool.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions.

Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @ onepeloton.com email address.

If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence.

Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.