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Lyft has an opening for a PhD Machine Learning Software Engineer Intern (Summer 2027), based in California. It is an internship on site. The advertised pay is $65 to $68 an hour.
The description below comes from Lyft's own job posting.
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 over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with petabyte-scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business.
As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue.
If you are a PhD student who enjoys turning open-ended research questions into working systems, and you want your research to be tested against real users and real data, this opportunity is for you!
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.
The expected base pay range for this position in the San Francisco area is $65-$68/hour. 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.
Total compensation is 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.
Lyft advertises $65 to $68 an hour for this role.
No, it is an on-site job in California.
The posting mentions a phd or doctorate or equivalent and skills such as Python, SQL, Spark and Machine Learning. Read the full description above for the complete list.
Use the apply button on this page. It takes you to Lyft's own application form, so your CV goes directly to their hiring team.
Lyft published the role on October 6, 2026. We check the employer's job board every day and take this page down when the role closes, so if you can read it, the job was still listed at our last check.
Source: Lyft careers page (app.careerpuck.com). Applications go straight to the employer. We check the listing daily and remove it once it closes.
Wherever you’re headed, count on Lyft for rides in minutes. The Lyft app matches you with local drivers at the tap of a button. Just request and go. Ride by ride, we’re changing the way our world works. We imagine a world where cities feel small again. Where transportation and tech bring people together, instead of apart. We see the future as community-driven - and it starts with you.
Industry: Transportation & Logistics
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