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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.
If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science.
Responsibilities:- Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions.
- System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems.
- Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically evaluating new research and identifying high-impact use cases across business areas.
- Collaboration: Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals.
- Data-Driven Decision Making: Leverage data-driven insights to inform and refine ML strategies and solutions.
- Mentorship & Technical Leadership: Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration.
- Code Quality: Write production-level code and participate in code reviews to ensure quality and share knowledge across the team.
- M.S. or Ph.D. in Computer Science or related technical field
- 5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields
- Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
- Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning
- Experience with translating state-of-the-art ML research into production systems
- Proficiency in Python, Golang, or other programming language
- Proven ability to tackle ambiguous problems and deliver solutions at scale.
- Strong communication and interpersonal skills for effective cross-functional collaboration.
- 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 $149,600-$187,000 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 job fills an existing vacancy.
Skills Required
- B.S., M.S. or Ph.D. in Computer Science or related technical field or relevant work experience.
- 8+ years (or Ph.D. with 6+ years) of experience in machine learning, data science, or related fields.
- At least 3 years in a senior or staff engineering role.
- Experience in machine learning workflows and large language models (LLMs).
- Deep understanding of supervised/unsupervised learning, reinforcement learning, and advanced optimization techniques.
- Deep knowledge of ML libraries like scikit-learn, TensorFlow, PyTorch, Keras.
- Experience with distributed computing frameworks such as Spark and Hadoop.
- Strong knowledge of cloud platforms (e.g., AWS, GCP) and containerization tools (Docker, Kubernetes).
- Proven ability to quickly and effectively turn research ML papers into working code.
- Practical knowledge of building efficient end-to-end ML workflows and deploying models to production.
- Strong communication, interpersonal skills, and proven mentorship/technical leadership.
- Ability to write production-level code and participate in code reviews.
Lyft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lyft and has not been reviewed or approved by Lyft.
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Healthcare Strength — Corporate materials describe comprehensive medical, dental, and vision coverage with added access to One Medical and mental-health support, indicating a solid core health offering. This breadth positions health benefits as a relative strength for full-time employees.
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Parental & Family Support — Company information highlights paid parental leave for new parents, with flexibility in how time can be taken. This signals strong family support within the corporate package.
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Leave & Time Off Breadth — U.S. salaried employees have unlimited paid time off alongside company holidays, and hourly roles receive structured PTO and sick time. These policies point to ample time-off availability compared with many roles.
Lyft Insights
What We Do
Lyft was founded in 2012 by Logan Green and John Zimmer to improve people’s lives with the world’s best transportation, and is available to approximately 95 percent of the United States population as well as select cities in Canada. Lyft is committed to effecting positive change for our cities by offsetting carbon emissions from all rides, and by promoting transportation equity through shared rides, bikeshare systems, electric scooters, and public transit partnerships.
