Note: The job is a remote job and is open to candidates in USA. Diligent Robotics is a company that envisions a future powered by robots working seamlessly with human teams. They are seeking a Sr. ML Engineer, Autonomous Navigation to develop learning-based navigation models for their service robot, Moxi, enhancing its ability to navigate safely around people and equipment.
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
Skills
- 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
- Experience with Vision-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control
- Strong proficiency in PyTorch and experience with sequence models / policy learning
- Experience with imitation learning and/or reinforcement learning in robotics or autonomy contexts
- Experience with socially-aware navigation, dynamic obstacle avoidance
- Experience with RL at scale (simulation rollouts, distributed training, stability/debugging)
- Familiarity with ROS navigation stacks and safety constraints for mobile robots
- Experience building eval harnesses (offline replay, scenario libraries)
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