Staff, ML Engineer - E2E

Experience developing E2E or mid-to-end models for autonomous driving, ADAS, or robotics.

Familiarity with differentiable cost maps, latent space planning, or behavior cloning / reinforcement learning in driving domains.

Publications or open-source contributions in top-tier ML or robotics venues (CVPR, NeurIPS, ICLR, ICRA, CoRL).

$209,300-313,800 CAD

As a Staff Machine Learning Engineer focused on End-to-End (E2E) Model Development, you will lead the design and deployment of learning-based architectures that connect perception inputs to driving decisions — advancing the frontier of closed-loop autonomous driving performance.

You’ll architect and push forward Torc’s End – to – End approaches through unified, differentiable pipelines, leveraging massive real-world and simulated datasets to continuously improve system intelligence.

This is a high-impact technical leadership role focused on core model research and large-scale ML development, not feature-layer logic or rule-based planning.

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.

Now a part of the Daimler family

, we are focused solely on developing software for automated trucks to transform how the world moves freight.

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.