Senior Machine Learning Engineer, Diligent Robotics

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus)
• 5+ years of experience in ML for robotics and/or autonomous vehicles.
• Strong proficiency in PyTorch and experience with sequence models / policy learning
• Experience with imitation learning and/or reinforcement learning in robotics or autonomy contexts

Desirable

• As an ML Engineer II (Navigation), you will develop learning-based navigation models that enable Moxi to move naturally and safely around people, beds, wheelchairs, and equipment
• You’ll train policies using fleet data (imitation learning) and refine behavior with simulation and RL. Your work will directly impact delivery speed, reduced hesitation/deadlocks, and fewer interventions in real hospital deployments
• 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