Director, Engineering, Autonomous Vehicles

What you'll do

• Define the technical vision and architecture for a next-generation autonomous driving stack combining classical and learning-based approaches.
• Build and lead a high-performing engineering organization across prediction, decision making, planning, control, and safety.
• Integrate classical safety-critical autonomy with large-scale learned systems into a unified production platform.
• Develop robust system-level safety architectures including redundancy, fallback, and degraded-mode strategies.
• Lead the development of end-to-end, data-driven autonomous driving pipelines from perception through vehicle operation.
• Advance and integrate vision-language-action (VLA) and driving foundation models into production vehicles.
• Translate research breakthroughs in robotics, embodied AI, and generative AI into scalable self-driving technologies.

What we're looking for

• A PhD with experience, an MS with , or a BS with relevant industry experience is required.
• Candidates must have at least 8 years of experience leading a team.
• Significant technical leadership experience managing senior engineers, architects, and engineering managers on production systems is required.
• Extensive knowledge of traditional driverless vehicle system designs including prediction, planning, decision making, control, safety, redundancy, and fallback systems is required.
• A solid grasp of modern learning-based autonomy, including end-to-end driving models, foundation models, large-scale machine learning, or embodied AI is required.
• Experience building hybrid AV architectures combining classical safety systems with end-to-end learned driving is preferred.
• Experience with CUDA, GPU computing, and accelerated AI infrastructure is preferred.
• A record of technical leadership through patents, publications, or significant contributions to robotics and autonomous vehicle technology is preferred.