Apply machine learning and vehicle dynamics expertise to control problems within an AI-first self-driving engineering team. Work spans simulation and on-vehicle validation.
As a Senior Machine Learning Engineer, you will develop learned vehicle behavior models and integrate them into closed-loop simulation. You will improve controller adaptation across vehicles and operating conditions using Python, C++, and PyTorch. The work combines control theory, agile systems, physical hardware, and modern machine learning. You will own problems from conceptualization through experimentation, simulation, and validation.
Key Responsibilities: Design learned approaches for vehicle control problems
Develop vehicle behavior and dynamics models
Integrate learned models into closed-loop simulation




Build data pipelines, metrics, and evaluation tooling
Validate algorithms on vehicles and compare classical baselines
Requirements: MS, PhD, or bachelor's degree in a technical field
Four or more years of relevant industry experience with bachelor's degree
Depth in control theory and dynamic systems
Production-quality Python and C++ coding skills
Machine learning experience with physical hardware and PyTorch
Use control theory, machine learning, and production coding to advance vehicle dynamics through validated self-driving systems.

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📌 Senior Vehicle Dynamics Machine Learning Engineer (Manitoba)
🏢 Waabi
📍 Manitoba