data
Posted 2 weeks agoSenior Machine Learning Engineer, Recommendations
at lyft
Toronto, CanadaHybrid
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.
Requirements
- 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.
- 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.
- You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities:
- 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.
- M.S. or Ph.D. in Computer Science or related technical field
- 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.
- Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.
Benefits
- Extended health and dental coverage options, along with life insurance and disability benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy.
- 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
- Your recruiter can share more information about the various in-office perks Lyft offers.
- 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.
Additional details
- 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.
- This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation.
- 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.
- 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:
- Strong communication and interpersonal skills for effective cross-functional collaboration. Benefits:
- RRSP plan with company match to help save for your future
- The policy allows team members to take off as much time as they need (with manager approval).
- Lyft is committed to creating an inclusive workforce that fosters belonging.