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, dynamic systems, physical hardware, and up-to-date 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.