Six Figure Work

Senior Machine Learning Engineer, Recommendations

Lyft

Company websitelyft.com (Lyft, opens in new tab)

Base salary $162,800  to $203,500

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (10 min ago) · observed since

About this job

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 paid parental leave. Biological, adoptive, and foster parents are all eligible
  • Subsidized commuter benefits
  • Monthly Lyft credits and complimentary Lyft Pink membership

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.

Source: Lyft on Greenhouse · View original posting (opens in new tab)

Pay in context

This role's base floor ($162,800) is above 27% of the 1,492 Data & ML roles in California listed on this site. Their median floor is $190,000; the middle half runs from $160,000 to $229,900.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.

This range next to 6 other live Lyft roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Lyft roles with the nearest advertised base floor
RolePublished base
Senior Machine Learning Engineer, Recommendations (this listing)$162,800 - $203,500
Counsel, Patents & IP$161,920 - $202,400
Counsel, Patents & IP$161,920 - $202,400
Sr. Manager, GTM Strategy & Sales Packaging$169,000 - $211,250
Sr. Manager, GTM Strategy & Sales Packaging$169,000 - $211,250
Firmware Engineering Manager, Lyft Urban Solutions$176K - $220K
Staff Engineer, Luxury$176K - $220K

Same $100K to $400K scale as every card. All Lyft roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
  3. Stopped meeting the published-salary criteria
  4. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-02-20
Where this pay comes from

Location as the employer wrote it: San Francisco, CA

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 benef

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.