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.

Data and Machine Learning are at the heart of Lyft’s products and decision-making. As a member of the Machine Learning team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Machine learning engineers build systems that make our products predictive, personalized, and adaptive. We’re looking for passionate, driven engineers to take on some of the most interesting and impactful problems in ridesharing.

As a machine learning engineer on the Rider, Recommendations team, 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
• Be able to make effective tradeoffs between model accuracy and its productization complexity and runtime performance. 
• Develop statistical, machine learning, or optimization models
• Write production quality code to launch machine learning models that can scale well to serve millions of requests per day
• Evaluate machine learning systems against business goals
• 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
• 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
• Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Access to a Health Care Savings Account
• In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service 
• 4 Floating Holidays each calendar year prorated based off of date of hire
• 10 paid sick days per year regardless of province
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. 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 now if you wish to make such a request.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.

The expected base pay range for this position in the Toronto area is $98,000 - $135,000 CAD. 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.