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With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a backend Software Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and 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 building an AI Platform at scale, with applications across each facet of the company, we are searching for you.
If you are a creative and critical thinker with experience in AI and 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:
- Independently own and deliver features with well-defined scope
- 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
- Ensure comprehensive testing and code quality for your features, including unit and end-to-end tests
- Monitor the stability and performance of deployed code, proactively identify and fix bugs, and support SEVs when necessary
- Write clear technical documentation, including technical specs within expected scope, runbooks, and onboarding documentation
- Accurately evaluate assigned tasks and features for effort estimation and listen to roadmapping discussions, contributing feedback as needed.
- BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
- 3+ years of backend experience working in any of these stacks; Python, GO, Java, etc.
- Nice to Have: Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
- Nice to Have: Experience with AI assisted coding such as Cursor or Claude Code
- 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 $108,000-$135,000 CAD, 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 is a new position.
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