Applied Robotics Engineer

Highlights

• Bridge frontier action and world models from simulation to real hardware deployment.
• Deploy AI under real-world constraints like limited compute and noisy sensors.
• Partner in the field to integrate models with legacy control and sensor systems.

What they offer

• Equity

Ideal candidate

A hands-on roboticist who thrives at the hardware-software boundary and owns systems end-to-end through failure. Rigorous about evaluation and comfortable in the field explaining what models will and won't do.

Requirements

• 5+ years of experience deploying AI or robotics systems from prototype to production, spanning simulation, model development, and real-world deployment
• Owned model deployment from training checkpoint to running on real hardware end-to-end, including failures
• Experience debugging subtly wrong models and fixing root-cause system issues
• Strong Python and PyTorch, with ability to drop into C++ for performance
• Experience with inference optimization on constrained hardware including quantization, distillation, TensorRT or ONNX export
• Depth in policy learning and control, world models and simulation, or perception and inverse dynamics models
• Experience across hardware-software boundary including sensors, middleware, edge compute and real-time constraints
• Rigorous about evaluation and understanding benchmark limitations
• Comfortable working with partner engineers and leadership and communicating model capabilities