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Active1mo ago

Machine Learning Engineer, Safety and Customer Care AI

LyftΒ·πŸ“ Toronto, Canada

Employment

FULL TIME

Work mode

On-site

Experience

MID LEVEL

Salary

From C$1.4M/yr

Role overview

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. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data

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Role market pulse

How Machine Learning Engineer demand looks in Canada

51/100 Β· steady

Live jobs

31

Posted 30d

13

30d movement

-27.8%

Remote share

19.4%

Salary listed

77.4%

Salary trend 1Y

Not enough history

What they are looking for

Skills & requirements

Qualification

Build and scale evaluation frameworks, golden sets, rubric-based grading, LLM-as-judge where appropriate, and regression testing; Experience: 3+ years of industry experience in applied ML/AI, inclusive of an MS or PhD in Computer Science, Machine Learning, Artificial Intelligence or a related technical field; Experience with AI/LLM evaluation; PhD in Computer Science, Machine Learning, Statistics, or a related technical field

Department Β· SCC Tech

L

Hiring company

Lyft

Technology

Wherever you’re headed, count on Lyft for rides in minutes. The Lyft app matches you with local drivers at the tap of a button. Just request and go. Ride by ride, we’re changing the way our world works. We imagine a world where cities feel small again. Where transportation and tech bring people together, instead of apart. We see the future as community-driven β€” and it starts with you.

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