Waabi is hiring a Senior / Staff ML Engineer in Toronto!
Waabi is hiring a senior or staff-level machine learning engineer for its Toronto team, focused on bringing learned methods into the vehicle control stack for autonomous driving. The role sits at the intersection of classical control and modern ML: the goal is to replace or augment hand-tuned approaches with data-driven models that generalize across vehicles and driving conditions. This is an end-to-end ownership position on a safety-critical system, spanning offline experimentation, closed-loop simulation and validation on real vehicles, and it involves close collaboration with a multidisciplinary group of engineers and research scientists pursuing an AI-first approach to scaling safe self-driving.
Key responsibilities
- Design and build ML and data-driven approaches for vehicle control problems traditionally handled by classical methods
- Develop learned models of vehicle behavior and dynamics and wire them into closed-loop simulation
- Improve how the controller adapts across different vehicles and operating conditions using machine learning
- Own problems end to end, from initial concept and offline experiments through simulation and on-vehicle validation
- Build data pipelines, evaluation metrics and tooling to determine whether a learned approach beats the classical baseline
- Contribute to technical and architecture discussions, helping define how learning and classical control coexist in a safety-critical stack
Key requirements
- MS, PhD, or Bachelor's degree in Robotics, Controls, Mechanical or Electrical Engineering, Computer Science or a related field, plus at least 4 years of industry experience
- Demonstrated depth in control theory and dynamic systems, such as MPC, optimal control, state estimation, system identification, and kinematic or dynamic vehicle modeling
- Hands-on experience applying machine learning to a physical system with real hardware in the loop, not simulation alone
- Production-quality Python and C++ coding ability, with experience in deep learning frameworks such as PyTorch
- Strong problem-solving grounded in linear algebra, optimization, statistics and probability
- Ability to prototype and test new algorithms quickly and design experiments that demonstrate whether they work
- Collaborative, open-minded team player who is passionate about self-driving technology and hard problems
- Seniority: Senior / Staff
- Work mode: Not specified
- Key skills: Python, C++, PyTorch, Control theory, MPC, Optimal control, State estimation, System identification, Vehicle dynamics modeling, Deep learning, Simulation, Data pipelines, Evaluation metrics
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