Staff Software Engineer (Learned & Hybrid Behavior Planning)

Join our team as a Staff Software Engineer, where you will play a crucial role in integrating learned models into behavior planning for autonomous driving. You will work closely with ML engineers and autonomy teams, shaping how machine learning improves autonomy behavior while ensuring safety and deployability. Your responsibilities will include leading the integration of learned models into the behavior planning stack, collaborating with ML teams, designing integration strategies, defining validation criteria, and debugging model behavior. This is a high-impact role for someone with a strong background in autonomous vehicles, robotics, or a related autonomy domain.

• Lead the integration of learned models into the behavior planning stack for autonomous driving, ensuring safety and measurability.
• Collaborate with machine learning teams to improve models and define validation, fallback, monitoring, and safety criteria for learned planning components.
• Mentor other engineers and lead technical designs, while debugging and analyzing model behavior using various tools and data.
• This is a high-impact role for someone who understands both the practical constraints of real-world planning systems and the opportunities enabled by modern learned models
• Ability to reason about safety, system behavior, evaluation, and deployment risk
• Experience working with heuristic or classical planning systems
• Strong experience in autonomous vehicles, robotics, or a related autonomy domain
• Strong software engineering skills with proficiency in C++. Python proficiency is a plus
• Deep technical background in behavior planning, decision-making, or motion planning
• Excellent cross-functional communication and technical leadership skills
• Experience integrating or developing learned behavior policies, behavior classification, trajectory prediction, or actor intent models