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Added 2 mins ago
SC
Senior Business Analyst
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- Full-time
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CH
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Develop specifications and prepare cost estimates for requests for proposals.
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- Full-time
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Added 17 mins ago
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- Full-time
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Lead initiatives that make our platform more reliable, faster, and more cost-efficient
Added 17 mins ago
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Senior iOS Engineer
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Toronto, ON · Vancouver, BC
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Added 17 mins ago
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Toronto, ON · NORTH YORK, ON
- Full-time
Complete all financial reporting including payroll, period summaries and sales reports in a timely and accurate manner, maintain appropriate budgetary, cost and inventory controls.
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Added 31 mins ago
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Project Coordinator
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Added 31 mins ago
BC
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- Full-time
…purchasing decisions for major projects. You’ll play a key role in cost control, risk management and schedule adherence within a multidisciplinary and international…
Added 31 mins ago
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Added 31 mins ago
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Added 31 mins ago
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Lyft

Senior Machine Learning Engineer, Recommendations

Toronto, ON, Canada

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Job details

Experience: 5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields
Posting language: English
Posted: Oct 6, 2026

Original job description

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.

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 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.

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More about this job

Responsibilities

The role involves designing, building, and deploying scalable machine learning models for real-time applications while architecting reliable ML pipelines. You will also provide technical leadership, mentor junior engineers, and collaborate across teams to align ML initiatives with business goals.

Requirements

Candidates must hold an M.S. or Ph.D. in Computer Science or a related field with at least 5 years of experience in machine learning modeling. Proficiency in Python or Golang, deep learning frameworks, and the ability to translate research into production systems are required.

Skills

Machine learning
Deep learning
Recommendation systems
TensorFlow
PyTorch
Python
Golang
System architecture
LLMs
Statistical analysis
Regression analysis
Hypothesis testing
Data science
Technical leadership
Mentorship
Production-ready deployment

Benefits

Extended health and dental coverage
Life insurance
Disability benefits
Mental health benefits
Family building benefits
Child care benefits
Pet benefits
Health Care Savings Account
RRSP plan with company match
Flexible paid time off
Paid parental leave
Subsidized commuter benefits
Lyft ride credits

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Artificial Intelligence
Recommendation Systems
Deep Learning
TensorFlow
PyTorch
Python
Golang
LLMs
Data Science
System Architecture
ML Pipelines
Regression Analysis
Hypothesis Testing
Production Engineering
Applied AI
Software Engineering
Technical Leadership
Mentorship
Ride-sharing
Data-driven decision making
Scalable systems
Algorithm development
Research to production
Cross-functional collaboration

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