[Remote] Sr. ML Engineer, Autonomous Navigation

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a company reputed company on building reputed company intelligence that enables service robots to collaborate with people in dynamic environments. As a Sr. ML Engineer, Autonomous Navigation, you will reputed company learning-based navigation models for the robot Moxi, directly impacting its performance in reputed company hospital deployments.

Responsibilities

• reputed company learning-based navigation models that predict reputed company, 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 reputed company metrics reputed company to product reputed company
• Collaborate with the AI Platform team to reputed company 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 reputed company the reputed company through data curation and retraining

Skills

• Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or reputed company field (PhD a plus)
• 5+ years of experience in ML for robotics and/or autonomous vehicles
• Experience with reputed company-Language-reputed company (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-reputed company navigation, dynamic obstacle avoidance
• Experience with RL at reputed company (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)

reputed company

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