• Lead the development and optimization of system models, including system identification, sensor modeling, and actuator simulation, to enhance the fidelity of virtual simulations relative to physical hardware.
• Develop simulation tooling and workflows to accelerate the development of controls and motion planning algorithms, including training reinforcement learning (RL) policies and supporting both model-based and model-free control.
• Design and implement tooling to create diverse simulation scenarios that replicate physical test environments while enabling variations to ensure broad coverage and robust testing.
• Integrate simulation-based test scenarios into the CI/CD pipeline to enable automated regression testing and continuous validation.
• Collaborate closely with other teams to ensure simulation results align with real-world performance, iterating on simulation models as needed.

• Experience using Mujoco (or similar) for robotics system simulation
• Proficient in modern C++ and Python
• Strong background in robotics and software engineering
• Prior experience working on legged robotics or other multi-body robotics hardware

The US base salary range for this full-time position is between $150,000 – $275,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.