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At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging Machine Learning and AI to better serve our customers. The Machine Learning Platform team is seeking a Software Engineer interested in contributing to our platform which supports real-time, online, and offline ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.
If you are interested in hands-on exposure to classical machine learning models, production ML systems at scale, with applications across each facet of the marketplace and business, we are searching for you.
If you are a creative and critical thinker with an interest or experience in machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
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 $108,000 - $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging Machine Learning and AI to better serve our customers. The Machine Learning Platform team is seeking a Software Engineer interested in contributing to our platform which supports real-time, online, and offline ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.
If you are interested in hands-on exposure to classical machine learning models, production ML systems at scale, with applications across each facet of the marketplace and business, we are searching for you.
If you are a creative and critical thinker with an interest or experience in machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
Responsibilities:
- Contribute to the roadmap and architecture based on technology and business needs
- Write well-crafted, well-tested, readable, maintainable code
- Have a good grasp and ability to explain the various tradeoffs made in decisions
- Participate in code reviews to ensure code quality and distribute knowledge
- Build Features from tech specification to positive execution
- Incorporate considerations for business context and failure modes in your work
- Proactively participate in resolving ongoing incidents
- Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
- Share your knowledge by giving brown bags and tech talks.
- BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience
- 3+ years of engineering experience working in any of these stacks; Python, GO, Java, etc.
- Experience with Linux
- 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 $108,000 - $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. 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
python
java
ai
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- Posted
- Jun 24, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Toronto
- Company
- Lyft
Industries
Ground Passenger Transportation
Categories
Engineering
Information Technology
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