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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.
Our engineering team is growing rapidly, and we are looking for a Machine Learning Engineer. As a machine learning engineer, 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. 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:
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 at least 3 days per week, including 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 Toronto area is CAD $96,800 - CAD $121,000, 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.
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.
Our engineering team is growing rapidly, and we are looking for a Machine Learning Engineer. As a machine learning engineer, 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. 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:
- 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
- 2+ 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
- Desire to learn and grow
- Understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits
- 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
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 at least 3 days per week, including 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 Toronto area is CAD $96,800 - CAD $121,000, 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.
Key Skills
Ranked by relevance
machine learning
deep learning
data analysis
storage
python
golang
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- Posted
- Dec 12, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Toronto
- Company
- Lyft
Industries
Ground Passenger Transportation
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
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