Vehicle Motion Control AI/ML Platform Design Engineer
About The Position
Join General Motors at an exciting time of transformation in vehicle motion control. We are building a culture of inclusion, innovation, and collaboration, with opportunities to develop advanced control, estimation, and AI/ML solutions that impact real-world vehicle systems. As a Vehicle Motion Control AI/ML Platform Design Engineer, you will design and implement advanced control, state estimation, and data-driven algorithms for vehicle motion systems, including steering, braking, propulsion, rear steering, active aerodynamics, and integrated chassis functions. You will work on model-based design, simulation, and AI/ML-enabled algorithm development to create robust, modular, and high-performance motion control solutions. This role is ideal for engineers who want to apply strong controls and estimation fundamentals while growing hands-on experience in machine learning for real-time vehicle systems.
Requirements
- Solid foundation in classical control methods such as PID, state feedback, and observers.
- Knowledge of advanced control strategies such as adaptive control, model predictive control, learning-based MPC, and ML/AI-based control approaches.
- Strong knowledge of state estimation and observer design.
- Experience with sensor fusion methods, including Kalman filter variations such as EKF, UKF, and particle filters, and understanding of system identification and parameter estimation in dynamic systems.
- Hands-on experience using Python for data analysis and model development, with exposure to ML frameworks such as PyTorch, TensorFlow, scikit-learn, and NumPy/pandas.
- Experience or a strong interest in applying machine learning or data-driven modeling to control, estimation, and system dynamics problems.
- Experience with model-based design and vehicle dynamics simulation tools such as CarSim, CarMaker, or equivalent.
- Working knowledge of embedded software development in C/C++, MATLAB/Simulink, and code generation for production-oriented development.
- Familiarity with vehicle communication and measurement tools such as Vehicle SPY, INCA, and CANalyzer.
- M.S. or Ph.D. in Controls, Robotics, Aerospace, Mechanical Engineering, Electrical Engineering, Computer Engineering, Applied Mathematics, or a related field with relevant experience.
- Strong analytical and problem-solving skills.
- Demonstrated ability to communicate clearly through technical reports and presentations and to collaborate effectively across teams.
- Valid driver’s license for occasional test support.
Nice To Haves
- Experience with reinforcement learning, model-based RL, or data-driven dynamics modeling for real systems.
- Familiarity with deep learning approaches such as CNNs, RNNs, or transformer-based models for estimation, prediction, or decision-making problems connected to motion control.
- Awareness of automotive safety concepts relevant to AI/ML-enabled control, including ISO 26262, SOTIF, runtime monitoring, and safe fallback strategies.
- Experience with requirements and interface definition tools such as DOORS, DNG, or Jama, and familiarity with automotive release and specification processes.
- Knowledge of related automotive systems such as powertrain, driveline, and CAN/LIN networks, plus exposure to advanced test setups such as dSPACE HiL, DiL, and in-vehicle track testing.
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, learned models, observers, and estimators.
- Support integration and testing in simulation environments such as CarSim, CarMaker, and Simulink, as well as HIL, SIL, and DiL setups.
- Contribute to data collection, curation, labeling, feature engineering, and analysis from simulation, proving grounds, and vehicle testing to support training and validation activities.
- Implement and evaluate AI/ML components in motion control loops with attention to safety, stability, and interpretability.
- Collaborate with cross-functional teams and deliver technical documentation, reports, and presentations.
- Participate in design reviews, peer reviews, and continuous improvement of development processes and technical standards.
Benefits
- Paid time off including vacation days, holidays, and supplemental benefits for pregnancy, parental and adoption leave.
- Healthcare, dental and vision benefits including health care spending account and wellness incentive.
- Life insurance plans to cover you and your family.
- Company and matching contributions to a Defined Contribution Pension plan to help you save for retirement.
- GM Vehicle Purchase Plan for you, your family, and friends.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
