Sr. ML Engineer, Autonomous Navigation
Core
Develop learning-based navigation models enabling service robots to move naturally and safely around people and equipment in dynamic hospital environments.
Role type
Senior IC machine-learning engineer (autonomous navigation)
Builds
Learning-based navigation policies and imitation learning pipelines for service robots
Domain
Robotics / Autonomous Systems / Healthcare
Deliverable
production ML models
Required skills
Imitation learning, Reinforcement learning, Behavior cloning, Transformer/diffusion policies, PyTorch, Sequence models, Policy learning, Trajectory prediction, Simulation-based refinement, Reward shaping, Domain randomization
Preferred skills
Socially-aware navigation, Dynamic obstacle avoidance, RL at scale, ROS navigation stacks, Eval harnesses, Offline replay, Scenario libraries
Responsibilities
Develop learning-based navigation models that predict safe, smooth trajectories from sensor inputs and/or perception representations. Build imitation learning pipelines from fleet logs (trajectory extraction, filtering, scenario balancing, evaluation). Implement simulation-based refinement (RL, reward shaping, domain randomization) to improve robustness. Define navigation success metrics aligned to product outcomes. Collaborate with the AI Platform team to integrate learned policies behavior/safety systems and validate on-robot. Build regression tests and scenario replay suites for challenging scenarios. Analyze field behavior, identify failure modes, and close the loop through data curation and retraining.
