Senior/Staff Software Engineer – ML-based Vehicle Controls

About the role

Design and develop data‑driven, machine‑learned approaches to vehicle control problems, bringing modern ML to a domain traditionally solved with classical methods. Join a multidisciplinary team of engineers and research scientists using an AI‑first approach to enable safe self‑driving at scale.

Key responsibilities

• Develop learned models of vehicle behavior and dynamics and integrate them into closed‑loop simulation.
• Apply machine learning to improve controller adaptation across vehicles and operating conditions.
• Own problems end‑to‑end, from conceptualization and offline experimentation through simulation and on‑vehicle validation.
• Build data pipelines, evaluation metrics, and tooling to measure learned approaches against classical baselines.
• Participate in technical and architecture discussions to define how learning and classical control coexist in a safety‑critical stack.

Required profile

• MS/PhD or Bachelor’s degree with at least 4 years of industry experience in robotics, controls, mechanical/electrical engineering, computer science, or related fields.
• Demonstrated depth in control theory and dynamic systems (e.g., MPC, optimal control, state estimation, system identification, vehicle modeling).
• Hands‑on experience applying machine learning to physical systems with real hardware in the loop.
• Production‑quality coding skills in Python and C++ and experience with deep‑learning frameworks such as PyTorch.
• Strong problem‑solving abilities using linear algebra, optimization, statistics, and probability.

Required skills

• Python
• C++
• PyTorch
• Model Predictive Control (MPC)
• Optimal control
• State estimation
• System identification
• Vehicle dynamics modeling
• Linear algebra
• Optimization
• Statistics
• Probability