Jobs / United States / Peloton Interactive INC
Machine Learning Engineer III
Peloton Interactive INC · 🇺🇸 New York, New York
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 30 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 34 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Peloton Interactive INC paid sponsored hires in similar roles6 certified filings for “Site Reliability Engineer III” (Software Developers) in NY: $161k–$190k, median $175k. Most were filed at wage level III (50%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Peloton Interactive INC
The US Department of Labor certified 30 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 34 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Peloton Interactive INC →
About the role
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 model monitoring • MS/PhD in highly quantitative fields including Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc. preferred • Comfortable working with near real-time ML applications, preferred • Proven track record of working with product managers to launch ML-based product features, preferred #LI-DD1 #LI-Hybrid 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, without limitation, experience and 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 eq