Teams at Dexmate

Lead development and analysis of high-fidelity finite element and multi-body dynamic models for robotic systems. Perform static, dynamic, durability, and MBD simulations, guide mechanical design with actionable insights, validate models with experimental testing, optimize structures for weight and stiffness, support failure investigations, and develop CAE workflows and best practices across multidisciplinary teams.

Perform research and develop learning-based manipulation, navigation, and control algorithms (RL/IL, perception, control) on simulators and real robots. Implement state-of-the-art models using deep learning frameworks, collaborate with cross-functional teams, and build robust manipulation skills for robot platforms.

Design, train, and deploy learned policies for robot manipulation and whole-body control. Build and operate training infrastructure, scale distributed GPU training, iterate between simulation and physical robots, debug failures, and collaborate with controls, embedded, and hardware teams to deliver production-ready robot learning systems.