Senior Applied Scientist, Safe Locomotion, Compass

Job description

We are seeking an Applied Scientist to join Amazon Robotics, Compass Team. In this role, you will own the development of safe legged locomotion algorithms and their deployment on physical hardware, developing learning-based controllers that enable quadrupeds and humanoids to walk, run, and recover from disturbances with agility and robustness. You will leverage Reinforcement Learning (RL), sim-to-real transfer, and other learning-based architectures to train policies that produce stable, dynamic gaits across varied terrains and operating conditions. These learned policies will interface with model-based control strategies to form whole-body control laws that balance performance and safety.

Job requirements

PhD, or Master's degree and 6+ years of applied research experience
3+ years of experience applying RL to physical robotic systems (beyond simulation-only work)
Demonstrated expertise in sim-to-real transfer for locomotion or manipulation tasks
Strong understanding of legged robot dynamics, contact mechanics, and whole-body control fundamentals
Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX) with experience building custom RL training pipelines
Experience with physics simulators for robotics (e.g., Isaac Gym/Sim, MuJoCo, PyBullet)
Track record of publications at top-tier venues (e.g., RSS, CoRL, ICRA, NeurIPS, ICLR, IROS)
Experience deploying RL-trained locomotion policies on physical quadrupeds or humanoids

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Senior Applied Scientist, Safe Locomotion, Compass

Job description

Job requirements

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