Senior Manager, ML Occupancy Modeling, Autonomy

We are seeking a Senior Manager of Machine Learning to build and lead a team focused on occupancy modeling as a core output of our end-to-end autonomy model. This team will develop learned representations of the driving scene that capture static and dynamic occupancy, freespace, uncertainty, and future scene evolution to support safe and scalable autonomous driving.

As a leader on the Autonomy team, you will own the strategy, roadmap, execution, and team development for occupancy outputs within the Large Driving Model, our end-to-end autonomy architecture. The team’s work will directly influence downstream planning, simulation, validation, and closed-loop vehicle behavior.

Key areas of responsibility include:

• Build and lead a small, high-performing ML team focused on occupancy outputs for our end-to-end autonomy model.

• Define the roadmap for occupancy modeling, including freespace, static and dynamic occupancy, occlusion reasoning, uncertainty, and future scene evolution.

• Partner closely with perception, planning, simulation, data, and ML infrastructure teams to make occupancy outputs useful for real-world autonomy.

• Guide model development, training, evaluation, debugging, and deployment of large-scale autonomy ML systems.

• Establish clear metrics and workflows that connect occupancy quality to downstream planning, safety, and closed-loop performance.

• Mentor engineers, set strong technical standards, and communicate progress and tradeoffs clearly across the organization.

• B.S., M.S., or Ph.D. in Computer Science, Robotics, Machine Learning, or a related field.

• 8+ years of experience building ML systems, ideally in autonomy, robotics, perception, prediction, planning, or simulation.

• Experience managing or technically leading ML engineers or researchers.

• Strong understanding of modern autonomy ML systems, including transformer models, multi-task learning, sensor fusion, or end-to-end driving models.

• Experience with learned scene representations such as occupancy, freespace, BEV perception, semantic maps, trajectories, or world models.

• Strong ability to turn ambiguous technical problems into clear team roadmaps and execution plans.

• Strong engineering background, with fluency in Python and experience working with production ML systems.