Machine Learning Engineer - Autonomous Driving Policy & Deployment

Inverted AI is a Vancouver-based UBC spin-out building the behaviour models behind autonomous driving. Our generative models of human driving are used by AV and ADAS companies for simulation, and we now train and deploy end-to-end driving policies that run onboard real vehicles. We have a large proprietary drone-captured driving dataset, abundant GPU compute, and a small, technically dense team of researchers and engineers.

The role

This is an early-career role for a strong engineer who wants to work on learned driving policies, from training runs on the GPU cluster to code that runs on the car. You'll work alongside our researchers, take ownership quickly, and grow your role with the company.

What you'll do

• Run, monitor and debug training of driving policy and perception models on multi-GPU clusters
• Build data pipelines that turn raw video and sensor logs into training data
• Help port, optimize and test models on embedded hardware, and integrate them with the vehicle software stack
• Build evaluation tooling and closed-loop simulation tests
• Maintain build systems, containers (Docker/Singularity) and CI for our Python and C++ codebases

Required qualifications

• BSc or MSc in Computer Science, Computer Engineering, Engineering Physics or similar (new and recent graduates welcome)
• Strong Python; working knowledge of C++
• Coursework or project experience with PyTorch and deep learning
• Comfortable on Linux, with git and Docker
• Self-starter who can contribute without a rigidly defined scope

Nice to have

• Robotics, autonomous racing (F1TENTH), RoboCup or similar student design-team experience, especially getting a model running on real hardware
• Experience with ROS/ROS 2, Jetson or other embedded GPUs, or real-time systems
• Reinforcement learning, imitation learning or computer vision projects
• Prior co-op or internship in ML or robotics

What we offer

• Salary: $90,000 - $120,000 CAD per year, depending on experience, plus participation in our employee stock option plan
• Health and wellness benefits and paid time off
• Your work runs on real vehicles, not just in benchmarks
• A small, fast-moving team with direct access to world-class ML researchers

Hiring process

A 30-minute remote screen with a short coding exercise; a 1-2 hour in-depth interview (in person if you're in Vancouver); a take-home with a programming and a design part, completed within a 48-hour window; then reference checks.

In person, downtown Vancouver, BC. Full-time. Must be legally entitled to work in Canada. Inverted AI is an equal opportunity employer. We welcome applicants from all backgrounds and make hiring decisions on qualifications, merit and business needs.