Lyft
Lyft~1mo ago

Machine Learning Engineer, Recommendations

Data ScienceMachine Learning EngineerDataData & AI
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Quick Summary

Key Responsibilities

Partner with Engineers, Data Scientists, Product Managers,

Technical Tools
Data ScienceMachine Learning EngineerDataData & AI

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 rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Trust & Safety, Growth and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building 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, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. 

As a machine learning engineer, you will be developing and launching the algorithms that power the platform’s core services and impactful products. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are hiring motivated experts in each of these fields. 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.

Responsibilities

~1 min read
  • 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
  • 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 We Offer

~3 min read
Extended health and dental coverage options, along with life insurance and disability benefits
Mental health benefits
Family building benefits
Child care and pet benefits
Access to a Lyft funded Health Care Savings Account
RRSP plan to help save for your future
In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
Subsidized commuter benefits

Location & Eligibility

Where is the job
Toronto, Canada
On-site at the office
Who can apply
Open to applicants worldwide
Listed under
Canada

Listing Details

First seen
March 25, 2026
Last seen
May 2, 2026

Posting Health

Days active
37
Repost count
0
Trust Level
31%
Scored at
May 2, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
Lyft
Lyft
greenhouse
Employees
5
Founded
2018
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LyftMachine Learning Engineer, Recommendations