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Open nowPosted 7 hours agoWe saw it 20 min after it went up

Software Engineer, Backend

Lyft174 open roles

Pay
CA$88,000 – CA$110,000 a year
Where
Toronto, Canada
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Your applicationOpen nowSoftware Engineer, BackendLyft · Toronto, Canada
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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Lyft postings stay open a median of 48 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 7 hours ago

Lyft median: 48 days open

The posting

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 at scale, leveraging Machine Learning to better serve our customers. The Machine Learning Platform (MLP) team is seeking a backend Software Engineer to help build and operate our platform, which supports real-time, online, and offline ML model execution, development, and iteration across Lyft. In this role, you will own well-defined tasks and contribute to features alongside a team of highly motivated Machine Learning and Software Engineers, learning from senior engineers while shipping production code that impacts systems across the entire business.

If you are interested in hands-on exposure to classical machine learning models and 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 in machine learning systems, eager to learn and grow as an engineer, and passionate about solving business problems using data in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

  • Own well-defined tasks and contribute to features on the ML platform, seeking guidance from senior team members when needed
  • Develop reliable, performant, well-tested, readable, maintainable code that follows team coding standards and meets feature requirements
  • Participate actively in code reviews, both giving and receiving feedback
  • Monitor the stability and performance of your code after deployment, and proactively fix bugs and debug issues within your scope
  • Participate in the team's operational responsibilities, including on-call rotations and following through on postmortem action items
  • Contribute to technical debt reduction and technology modernization efforts
  • Write documentation for the code and tasks you work on, including runbooks where needed, and help improve onboarding materials
  • Participate in postmortems and planning discussions, providing input and feedback
  • Collaborate with cross-functional partners, including the Machine Learning Engineers and Data Scientists who build on the platform
  • Build your understanding of the ML platform and the tradeoffs behind its design by working closely with senior team members
  • Utilize AI tooling to accelerate development workflows.

Experience:

  • BSc/MSc in Computer Engineering, Computer Science, or a related field, or relevant work experience
  • 1+ years of backend engineering experience (internships included) working in any of these stacks: Python, Go, Java, etc.
  • Experience with Linux
  • Nice to Have: Exposure to machine learning systems or ML serving/training/deployment infrastructure through coursework, projects, or work experience; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud)
  • Nice to Have: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

  • 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 with company match 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 and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 $88,000 - CAD $110,000, 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.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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