Director, Prediction and ML Planning

Motional

Pittsburgh (Allegheny County)

On-site

USD 288,000 - 396,000

Full time

14 days+

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Benefits offered by this job

Medical, dental, and vision insurance
401k with company match
Life and pet insurance

Job summary

Motional is seeking a Director of Behaviors to lead machine learning teams in Pittsburgh. This role involves setting technical roadmaps and overseeing teams in robotics and autonomy.

Ideal candidates have 5+ years in engineering leadership, deep expertise in machine learning, and a strong educational background in computer science or related fields. The position offers a hybrid work schedule and competitive salary between $288,000 and $396,000.

Qualifications

  • Proven leadership experience managing high-performing engineering teams.
  • Deep proficiency in machine learning related to robotics behaviors.
  • Experience guiding teams to build integrated models for decision-making.

Responsibilities

  • Oversee machine learning-based Prediction and Motion Planning teams.
  • Define technical roadmap for developing imitation and reinforcement learning approaches.
  • Mentor and scale multiple sub-teams of engineers and researchers.

Skills

Leadership in engineering teams
Machine learning expertise
Robotics systems knowledge
Project management
Collaboration skills

Education

M.S. or Ph.D. in relevant field

Tools

AI models
Data pipelines

Job description

About Motional

Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation.

Mission Summary

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.
Required Qualifications & Experience
  • Proven Leadership: 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.
  • Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.
  • ML Behavior Expertise: 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.
  • Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.
  • Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs).
  • Educational Background: 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, ICRA, IROS publications).
  • Experience building large-scale data pipelines and training infrastructure required to train large driving models.
Work Arrangement

We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote.

Compensation

Salary Range: $288,000 USD - $396,000 USD

Benefits include medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Equal Opportunity

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

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