Deep expertise in at least one of the following areas, with working knowledge across one or more of the others: robotic learning, including imitation learning, reinforcement learning, vision-language-action models, world models, or policy evaluation; AI training and inference infrastructure, including distributed training, inference engines, GPU kernels, or collective communication; robotics data and simulation systems, including multimodal dataset verification, synthetic data generation, simulation, data curation, or sim-to-real workflows. Experience building large-scale AI or robotics platforms used by multiple teams or external customers, or experience with real-world robot systems and operational challenges.