Oversee and unify the machine learning-based Prediction and Motion Planning teams
Establish a clear technical roadmap transitioning toward a unified Large Driving Model performing joint prediction and planning
Define the technical roadmap for developing state-of-the-art imitation learning and reinforcement learning approaches
Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers
Implement sustainable engineering practices that promote psychological safety and high technical velocity
Expected to publish work in conferences like CVPR, ICCV, ECCV, and Neurips
Partner closely with Perception, Infrastructure, and Systems Engineering to ensure integration onto the vehicle platform

5+ years of experience managing high-performing engineering teams
3+ years of experience managing multiple sub-teams within autonomous systems, robotics, or advanced AI organization
Deep theoretical and practical proficiency in machine learning applied to robotics behaviors
Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making
Strong understanding of the full lifecycle from research to vehicle deployment
Proven experience guiding teams toward building integrated models rather than decoupled, sequential pipelines
Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs)
M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field

Director, Prediction and ML Planning

Key skills