Senior / Staff Software Engineer, ML-based Controls

You will develop machine-learned approaches to vehicle control, vehicle dynamics models, and closed-loop simulation integrations. You will build data pipelines, evaluation metrics, and tooling, validate approaches on vehicles, and help define how learned and classical control work together.

Responsibilities

• Design and develop machine-learned approaches to vehicle control
• Develop learned models of vehicle behavior and dynamics
• Integrate learned models into closed-loop simulation
• Apply machine learning to controller adaptation
• Build data pipelines, evaluation metrics, and tooling
• Validate approaches through offline experimentation, simulation, and on-vehicle testing
• Contribute to technical and architecture discussions

Requirements

• At least 4 years of industry experience
• Knowledge of control theory and dynamic systems
• Knowledge of MPC, optimal control, state estimation, system identification, and vehicle modeling
• Experience applying machine learning to a physical system with hardware in the loop
• Python and C++ coding skills
• Experience with PyTorch
• Knowledge of linear algebra, optimization, statistics, and probability
• Experience prototyping and testing algorithms and designing experiments

Benefits

• Equity incentive awards
• Annual performance bonus