Teams at RoboForce

Lead the engineering and technical direction of embodied AI systems for physical robots, including onboard inference, data collection, teleoperation, and on-robot reinforcement learning. Deploy and evaluate learned policies in real time, integrate sensing, control, and compute, improve the data-to-action loop, collaborate across robotics and ML teams, and mentor engineers.

Develop and improve machine learning models for robotic manipulation, including VLA and world-action models. Build robot-learning data pipelines, conduct simulation and real-robot evaluations, and deploy optimized models for real-time onboard inference. The role involves multimodal learning, reinforcement learning, tactile and force-torque sensing, and close collaboration with robotics, hardware, and product teams. This is a full-time, 3–6 month internship requiring five days per week in the office.

Own full-cycle recruiting for technical and business roles across robotics and Physical AI. Partner with hiring managers to define hiring strategies, source specialized talent, design structured interviews, use data and AI tools to improve effectiveness, manage offers/closing, and build talent pipelines while representing the company professionally.