Jobs / United States / Lyft INC
Senior Machine Learning Engineer, Recommendations
Lyft INC · 🇺🇸 San Francisco, CA
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 75 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 99 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 Lyft INC paid sponsored hires in similar roles22 certified filings for “Software Engineer” (Software Developers) in CA: $150k–$188k, median $164k. Most were filed at wage level II (55%) — 2 lottery entries, ≈31% 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 — Lyft INC
The US Department of Labor certified 75 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 99 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 Lyft INC →
About the role
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: • Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. • System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. • Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically evaluating new research and identifying high-impact use cases across business areas. • Collaboration: Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals. • Data-Driven Decision Making: Leverage data-driven insights to inform and refine ML strategies and solutions. • Mentorship & Technical Leadership: Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration. • Code Quality: Write production-level code and participate in code reviews to ensure quality and share knowledge across the team. Experience: • • M.S. or Ph.D. in Computer Science or related technical field • 5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields • Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks • Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning • Experience with translating state-of-the-art ML research into production systems • Proficiency in Python, Golang, or other programming language • Proven ability to tackle ambiguous problems and deliver solutions at scale. • Strong communication and interpersonal skills for effective cross-functional collaboration. Benefits: • Great medical, dental, and vision insurance options with additional programs available when enrolled • Mental health benefits • Family building benefits • Child care and pet benefits • 401(k) plan with company match to help save for your future • In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off • 18 weeks of