Agentic AI ML Engineer – Safety & Customer Care (Hybrid)

The available sources do not contain information about the company name for rounx.com.; Toronto; Hybrid; CAD 119,000 - 149,000; Full time

Benefits offered by this job

Extended health and dental coverage

Mental health benefits

Family building benefits

Child care benefits

Lyft Health Savings Account with match

Flexible paid time off

Subsidized commuter benefits

Job summary

Lyft is seeking a Machine Learning Engineer for the Safety and Customer Care team to fine-tune and align models, build AI agents, and power scalable, safety-critical support solutions for riders and drivers.

You will work across data, ML, and product, delivering end-to-end agent systems with offline/online evaluation and production readiness. Hybrid, in-office Toronto-based role with strong emphasis on responsible AI and safety.

Qualifications

• 3+ years of industry experience in applied ML/AI, including an MS or PhD.
• Post-training experience with open-source models.
• Hands-on familiarity with fine-tuning and preference-tuning methods such as SFT, LoRA, RLHF, RLAIF, and RLVR.
• Agentic development experience.
• Shipped agents with LangGraph or equivalent frameworks.
• Experience with AI/LLM evaluation.
• Designed offline/online evaluation metrics 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.

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.

Skills

ML/AI engineering

Python

PyTorch

LangGraph

Agent development

RLHF

SFT

LoRA

RLAIF

RLVR

Education

MS/PhD in CS/ML/AI

PhD preferred

Tools

LangGraph

Job description

Lyft is seeking a Machine Learning Engineer for the Safety and Customer Care team to fine-tune and align models, build AI agents, and power scalable, safety-critical support solutions for riders and drivers.

You will work across data, ML, and product, delivering end-to-end agent systems with offline/online evaluation and production readiness. Hybrid, in-office Toronto-based role with strong emphasis on responsible AI and safety.