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Senior Machine Learning Engineer, Recommendations

Lyft

Lyft is also hiring for this role in Toronto, Canada.

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This role on the market

19 open recommendations roles across 13 companies are on ApplySarthi right now, most of them in Bengaluru (2).

What recommendations roles keep asking for: Machine learning (68%), Python (63%), Deep learning (47%), LLMs (47%), PyTorch (37%), Spark (37%), NLP (26%), TensorFlow (26%) — counted across their open postings here.

Machine Learning Engineer jobs in the United States · Machine Learning Engineer jobs in San Francisco · Remote Machine Learning Engineer jobs · Deep learning jobs · LLMs jobs · Machine learning jobs · PyTorch jobs

Lyft has 152 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for recommendations roles keep coming back to Machine learning, Python, Deep learning, LLMs. Practise those questions before you sit with Lyft.

Questions you are likely to be asked

  1. Why do you want to join Lyft?
  2. What is your experience with Machine learning? Tell me one thing you learned the hard way.
  3. How did you know your model was actually good, and not just good on your test set?
  4. Tell me about a time the data was messy or wrong. What did you do?
  5. How would you explain your model's result to someone who is not technical?

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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:

Experience:

Benefits:

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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Listed on greenhouse · posted 2026-02-20. ApplySarthi collects openings and links to application pages; the role is advertised by Lyft, not by us.