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.
The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings.
Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades.
To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end.
Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map.
Responsibilities:- Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact
- Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems
- Develop statistical, machine learning, or optimization models
- Write production quality code to launch machine learning models at scale
- Evaluate machine learning systems against business goal
- B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
- 5+ years of Machine Learning experience
- Passion for building impactful machine learning models leveraging expertise in one or multiple fields.
- Proficiency in Python, Golang, or other programming language
- Excellent communication skills and fluency in English
- Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits
- 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.
Lyft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lyft and has not been reviewed or approved by Lyft.
-
Healthcare Strength — Corporate materials describe comprehensive medical, dental, and vision coverage with added access to One Medical and mental-health support, indicating a solid core health offering. This breadth positions health benefits as a relative strength for full-time employees.
-
Parental & Family Support — Company information highlights paid parental leave for new parents, with flexibility in how time can be taken. This signals strong family support within the corporate package.
-
Leave & Time Off Breadth — U.S. salaried employees have unlimited paid time off alongside company holidays, and hourly roles receive structured PTO and sick time. These policies point to ample time-off availability compared with many roles.
Lyft Insights
Similar Jobs
What We Do
Lyft was founded in 2012 by Logan Green and John Zimmer to improve people’s lives with the world’s best transportation, and is available to approximately 95 percent of the United States population as well as select cities in Canada. Lyft is committed to effecting positive change for our cities by offsetting carbon emissions from all rides, and by promoting transportation equity through shared rides, bikeshare systems, electric scooters, and public transit partnerships.







