Director, Prediction and ML Planning

Role Description

Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.

As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion.

Core Responsibilities

• Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.
• Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments.
• Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.
• Publish: As part of this role, you will also be expected to publish stellar work in conferences like CVPR, ICCV, ECCV and Neurips.
• Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards.

Qualifications

• 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.
• Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.
• 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 (e.g., trajectory forecasting joint with ego-policy generation) 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 with a heavy focus on Machine Learning.

Preferred Qualifications

• Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.
• A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications).
• Experience building large-scale data pipelines and training infrastructure required to train large driving models.

Benefits

• Medical, dental, vision insurance.
• 401k with a company match.
• Health saving accounts.
• Life insurance.
• Pet insurance.
• Additional forms of compensation such as a bonus or company equity.

Salary Range

$288,000 — $396,000 USD