ML Software Engineer, Routing

Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes.

We are hiring a Machine Learning Engineer to join our Routing team. Our team builds and maintains Lyft's system responsible for providing routes for every ride request on our platform. We process millions of route requests per day and low latency, high reliability and high accuracy are paramount for our success.

If you are a critical thinker with experience in machine learning workflows and writing reliable code, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Our technology stack runs on AWS, Kubernetes, Go, Python/C++, Apache Airflow, Flink, and Kafka. We use AI to improve development productivity, optimize customer support workflows, and enhance operational efficiency — all without compromising code quality or security. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers.

Responsibilities:

• Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions
• Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance
• Develop statistical, machine learning, or optimization models
• Write production quality code that can scale well to serve millions of requests per day
• Participate in code reviews, design reviews, production on-call support and incident triaging process.
• Write well-crafted, well-tested, readable, maintainable code

Experience:

• B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
• 3+ years of Machine Learning experience
• Nice-to-have: Experience with big data processing / distributed data pipelines and tools such as Apache Airflow and Spark/Flink
• Proficiency in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
• Ability to work in distributed teams spread across time zones. (EST and PST)

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 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 $118,800 - CAD $148,500, 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.