MemberTechnicalStaff-SoftwareDevelopment

In this role, you will act as the primary specialist for physics engine internals and dynamics, developing high-fidelity, vectorized simulation environments for robotics locomotion, navigation, and interaction/manipulation. You will collaborate with hardware engineers to validate robot models and partner with research scientists to ensure numerical stability and physical accuracy for Sim2Real transfer. Your work focuses on tuning solvers, optimizing collision dynamics, and performing system identification to enable the training of robust robot control policies for complex, physical interactions. Key job responsibilities * Develop and maintain the shared simulation software framework, specifically owning the physics integration, robot state management, and control layers * Develop and optimize parallelized (vectorized) physics environments for high-throughput reinforcement learning (e.g., Isaac Lab, MuJoCo) * Tune physics engine parameters (solvers, friction, restitution) to support complex contact-rich scenarios required for dexterous manipulation and agile locomotion. * Implement and validate complex robot models (URDF/MJCF) involving precise actuator and sensor modeling * Collaborate with robot engineers and scientists to perform System Identification (SysID) to minimize the Sim2Real gap About the team At Frontier AI & Robotics (FAR), we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation mode