Vehicle Motion Control AI/ML Platform Design Engineer
Core
Design and implement advanced control, state estimation, and data-driven AI/ML algorithms for vehicle motion systems including steering, braking, and propulsion.
Role type
Vehicle Motion Control AI/ML Platform Design Engineer
Builds
Robust, modular, high-performance motion control solutions for real-world vehicle systems
Domain
Automotive / Vehicle Dynamics / Control Systems
Deliverable
production ML models
Required skills
Classical control methods (PID, state feedback, observers), Advanced control strategies (MPC, adaptive control), State estimation and observer design, Sensor fusion (Kalman filters, particle filters), Python for data analysis and model development, ML frameworks (PyTorch, TensorFlow, scikit-learn), Model-based design and vehicle dynamics simulation (CarSim, CarMaker, Simulink), Embedded software development (C/C++, MATLAB/Simulink), Vehicle communication tools (Vehicle SPY, INCA, CANalyzer)
Preferred skills
Reinforcement learning, Deep learning (CNNs, RNNs, transformers), Automotive safety concepts (ISO 26262, SOTIF), Requirements and interface definition tools (DOORS, Jama), Advanced test setups (dSPACE HiL, DiL)
Technologies
PyTorch, TensorFlow, scikit-learn, NumPy, pandas, CarSim, CarMaker, Simulink, C/C++, MATLAB, dSPACE
Responsibilities
Design and implement vehicle motion control, estimation, and AI/ML-enabled algorithms across multiple domains; Apply model-based design, simulation, and data-driven workflows to develop and validate control strategies; Support integration and testing in simulation environments (CarSim, CarMaker, Simulink, HIL, SIL, DiL); Contribute to data collection, curation, labeling, feature engineering, and analysis; Implement and evaluate AI/ML components in motion control loops; Collaborate with cross-functional teams and deliver technical documentation
Seniority
Mid-to-Senior, hands-on IC