Senior / Staff Machine Learning Engineer, Vehicle Dynamics

Highlights

• Bring modern ML to vehicle control traditionally solved with classical methods.
• Build learned models of vehicle dynamics for closed-loop simulation.
• Own problems end to end from offline experimentation to on-vehicle validation.

Ideal candidate

Controls or robotics engineer with 4+ years bringing ML to real hardware. Collaborative, experimental problem-solver passionate about safe self-driving at scale.

Requirements

• MS/PhD or Bachelor's with minimum 4 years industry experience in Robotics, Controls, Engineering, CS or similar
• Depth in control theory and dynamic systems including MPC, optimal control, state estimation and vehicle modeling
• Hands-on experience applying machine learning to physical systems with real hardware in the loop
• Production-quality coding in Python and C++ with deep learning frameworks such as PyTorch
• Strong foundation in linear algebra, optimization, statistics and probability
• Ability to rapidly prototype algorithms and design experiments to validate them