Teams at Menlo Inc.

Owns final assembly and test quality at a contract manufacturer from trial builds through mass production. Responsibilities include yield analysis, inspection criteria, outgoing quality, NPI phase-gate readiness, root-cause and corrective actions, process audits, non-conformance disposition, quality metrics, and continuous improvement. Partners with engineering and manufacturing teams to resolve defects and ensure products meet design and shipment requirements.

Design, train, and deploy reinforcement learning policies for humanoid manipulation, grasping, dexterous control, and whole-body coordination. Own the MuJoCo-based sim2real pipeline, including rewards, environments, contact modeling, and domain randomization. Test policies on real robot hardware, use telemetry to improve failures, and collaborate with locomotion, controls, and hardware researchers. Open-source robotics and reinforcement learning work where possible.

Design, train, and deploy reinforcement learning policies for bipedal and whole-body humanoid locomotion. Own the sim-to-real pipeline, reward design, domain randomization, MuJoCo training environments, and hardware validation. Improve balance, gait, recovery, and terrain robustness using real-robot telemetry. Collaborate with hardware, controls, and manipulation researchers, while contributing to open-source robotics and research publications.