Your mission & challenges

As Edge AI Engineer, you turn cutting-edge models into production-grade, on-device intelligence for our robots. You work hands-on at the intersection of machine learning, embedded systems, and robotics. Your focus is making models fast, lean, and reliable on the hardware we ship.

• Deploy at the edge: Take models from trained to deployed using quantization, pruning, distillation, and every trick it takes to make them fast and lean on embedded accelerator platforms (e.g. NVIDIA Jetson, Qualcomm IQ-series).

• Own the toolchain: Work across model export and inference optimization frameworks (e.g. ONNX, TensorRT, AIMET) and the SDKs that turn a model into a working robot behavior.

• Optimize to the metal: Profile, analyze, and tune models and runtimes to meet the latency, power, and memory budgets of each hardware target.

• Partner across functions: Work closely with Research, Hardware, Software, and Product to bring on-device AI from research to shipped product.

• Set the bar for quality: Build and maintain benchmarking, on-device evaluation, and performance regression testing across every hardware target we ship.