Senior Software Engineer - Autonomous Vehicles

Design and integrate planning frameworks that combine end-to-end learned driving models with classical trajectory planning and deterministic safety systems.

Develop runtime arbitration and safety enforcement mechanisms between AI-generated trajectories and rule-based safety constraints.

Build scalable architecture enabling large AI driving models to operate reliably within automotive compute, latency, and real-time execution constraints.

Develop execution frameworks that ensure AI-generated behaviors satisfy vehicle dynamics, collision avoidance, passenger comfort, and safety requirements in real time.

Define and implement safety-oriented planning capabilities including trajectory validation, fallback handling, runtime policy gating, and Minimum Risk Maneuver (MRM) strategies.

Partner closely with AI, planning, controls, and systems teams to productize learned driving models into deployable autonomous vehicle systems.

Analyze and debug complex autonomy edge cases involving uncertainty, model failure modes, planner disagreement, and real-world safety constraints.

Improve observability, reliability, and debuggability across large-scale autonomy planning systems operating in simulation and on-vehicle environments.

Drive architectural decisions balancing AI capability, system robustness, safety, and embedded deployment efficiency.

Influence next-generation autonomy architecture defining how foundation-model and learning-based driving systems coexist with production-grade safety-critical vehicle platforms.

BS, MS, or PhD (or equivalent experience) in Computer Science, Robotics, Electrical Engineering, AI/ML, or related technical field.

12+ years of relevant industry experience in autonomous systems, robotics, AI infrastructure, or safety-critical software systems.