# Machine Learning Engineer, Safety and Customer Care AI

**Company**: Lyft
**Location**: Toronto, ON
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: CAD $118,800 - CAD $148,500
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/lyft/jobs/8684440002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_dbe725ba-6ba

## Description

At Lyft, our purpose is to serve and connect.

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.

As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help.

## Responsibilities:

- Conduct literature review and build post-training framework and lifecycle.

- Curate and process human and synthetic data for SFT/LoRA/RLHF/RLAIF/RLVR, and iterate on model quality for real support and safety tasks.

- Develop, evaluate, and productionize AI agents, designing tools, state, and control flow in LangGraph (or equivalent) and taking them through the full agent development lifecycle.

- Build and scale evaluation frameworks, golden sets, rubric-based grading, LLM-as-judge where appropriate, and regression testing.

- Ship models and agents into real-time production, with the monitoring and guardrails needed to operate them safely at millions of interactions a month.

- Apply traditional ML (classification, ranking, gradient-boosted trees) where it's the right tool, and partner with product, ops, and data science to scope problems and define success metrics.

## 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.

- Post-training experience with open-source models.

- Hands-on familiarity with fine-tuning and preference-tuning paradigms such as SFT, LoRA, RLHF, RLAIF, and RLVR.

- Agentic development experience.

- Built and shipped agents with LangGraph or equivalent frameworks, and comfort with the full agent development lifecycle.

- Experience with AI/LLM evaluation.

- Designed metrics and built offline/online evaluation for generative systems.

- Experience deploying ML/AI applications to real-time production use cases.

- Strong programming skills in Python and hands-on experience with PyTorch.

## 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

## Skills

### Required
- Python
- PyTorch
- LangGraph
- Machine Learning
- Artificial Intelligence
- LLM evaluation
- Agentic development

### Nice to have
- Experience applying ML/AI to customer support or trust & safety workflows
- PhD in Computer Science, Machine Learning, Statistics, or a related technical field
- Publications at top-tier peer-reviewed research venues

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/lyft/jobs/8684440002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)