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.
Experience:- 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.
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 $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.
