WHAT WE’RE DOING ISN’T EASY, BUT NOTHING WORTH DOING EVER IS.

We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven, venture-backed team as we build out current and future generations of humanoid robots.
As a Sr/Staff Simulation Engineer, you will be responsible for designing, developing, and maintaining the simulation systems that power our robotics testing and validation pipeline. You’ll create environments and tools that enable us to evaluate the performance of our AI in realistic, repeatable, and explainable ways. Your work will directly impact the safety, reliability, and scalability of our robots in the field.

SKILLS AND EXPERIENCE

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus).
• 5+ years of experience in simulation for robotics, autonomous vehicles, or related domains.
• Strong software development skills in C++ and Python.
• Experience with simulation platforms such as Unity, Unreal Engine, Gazebo, Isaac Sim, Webots or equivalent.
• Background in modeling sensors (cameras, LiDAR, IMUs, etc.) and actuators for simulation.
• Experience integrating autonomy stacks into simulation environments.
• Familiarity with ROS/ROS2 and distributed robotics frameworks.
• Strong debugging and problem-solving skills, including root cause analysis in complex systems.
• Demonstrated ability to work cross-functionally with hardware, perception, and planning teams.
• Bonus: experience with HIL/SIL test frameworks, reinforcement learning in simulation, or large-scale distributed testing.

• Design and build simulation frameworks and tools to evaluate robot performance across diverse environments and use cases.
• Develop realistic sensor, actuator, and physics models to replicate real-world robot interactions.
• Integrate AI and autonomy software into simulation environments for validation and benchmarking.
• Collaborate with perception, planning, controls, and hardware teams to define simulation requirements and ensure fidelity to real-world systems.
• Automate large-scale simulation testing to assess performance, safety, and regression.
• Analyze results, identify edge cases, and feed findings back into AI and system development.
• Drive improvements in simulation infrastructure to increase scalability, reproducibility, and explainability.
• Support hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing pipelines.