Machine Learning Engineer, Lyft
Rider
CA$98-135k
More information about location
3 days a week in office
Ride sharing company
Be an early applicant
Ride sharing company
1001+ employees
Be an early applicant
CA$98-135k
More information about location
3 days a week in office
1001+ employees
Company mission
To improve people’s lives with the world’s best transportation.
Role
Who you are
- We’re looking for passionate, driven engineers to take on some of the most interesting and impactful problems in ridesharing
- We’re looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment
- B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
- 3+ 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
What the job involves
- As a member of the Machine Learning team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation
- Machine learning engineers build systems that make our products predictive, personalized, and adaptive. We’re looking for passionate, driven engineers to take on some of the most interesting and impactful problems in ridesharing
- As a machine learning engineer on the Rider, Recommendations team, you will be developing and launching the algorithms that power the platform’s core services
- Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse
- They cut across transportation, economics, forecasting, mapping, personalization, and adaptive control
- We are hiring motivated experts in each of these fields
- 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
- Be able to make effective tradeoffs between model accuracy and its productization complexity and runtime performance
- Develop statistical, machine learning, or optimization models
- Write production quality code to launch machine learning models that can scale well to serve millions of requests per day
- Evaluate machine learning systems against business goals
- Participate in code reviews, design reviews, production on-call support and incident triaging process
- Write well-crafted, well-tested, readable, maintainable code
Our take
Lyft has aimed for consistent growth, making sure to pitch itself as a more reliable and friendly ride-sharing option than its main competitor, Uber. Uber has a greater market share and operates globally, but Lyft hopes to compete by its focus on ride-sharing over Uber's more diversified business approach and as a more rider-friendly and greener alternative to Uber.
Operating only in the USA and Canada, Lyft is in a position of being less affected by global events than Uber but also more vulnerable to local conditions. As an example, while it doesn't face the regulatory hurdles around employment rights that Uber does, it is unable to balance out the cost of the unusually expensive US auto insurance across its operations.
In 2022, Lyft acquired PBSC Urban Solutions, a bike-share equipment and technology supplier, allowing Lyft to compete in new verticals and reaffirming its commitment to green transportation. It has also trialed and launched Lyft Assisted, where drivers help passengers from their door into the car to get to medical appointments. These developments chime well with Lyft's unique selling point as a friendlier and more environmentally aware ride-sharing app.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 14 rounds)
Jun 2018
$600m
LATE VC
Mar 2018
$200m
LATE VC
Total funding: $4.9bn
Company benefits
- Great medical, dental, and vision insurance options
- Mental health benefits
- In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
- 401(k) plan to help save for your future
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Pre-tax commuter benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
- Family building benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
Company HQ
China Basin, San Francisco, CA
Articles
Leadership
John Zimmer
(Co-Founder)Originally an Analyst at Lehman Brothers, Zimmer then founded Zimride which was a private ridesharing company that pivoted into Lyft.
Logan Green
(Co-Founder)Founded Zimride, a private ridesharing company which later pivoted into Lyft.
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