Robot Learning Intern

Responsibilities

• Develop new algorithms and methods for training AI models that enhance robot dexterity
• Conduct cutting-edge research across multiple disciplines including Robotics, RL/IL, control, and perception
• Design and implement state-of-the-art learning-based manipulation, navigation, and control algorithms on real robots
• Work with other teams to develop a diverse set of robust manipulation skills for robots, such as VLA and WAM

Requirements

• Currently enrolled in a PhD program or hold a master's degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field
• Passion for working with robots
• Research experience in embodied AI, robotics, computer vision, machine learning, or human-AI interaction
• Experience with deep learning frameworks such as PyTorch
• Solid understanding of SOTA robot learning techniques like reinforcement learning and imitation learning
• Experience with robot simulators such as Isaac Gym, Isaac Sim, SAPIEN, MuJoCo, or Drake
• Experience building systems based on machine learning and/or deep learning methods

Preferred Qualifications

• A track record of research with work published in top conferences and journals such as Science Robotics, IJRR, RSS, CoRL, ICRA, NeurIPS, ICML, ICLR, or CVPR

About the Company

Dexmate is building the foundation for physical AI — a unified platform that combines high-quality robotic hardware with a universal Physical AI OS, making robots as easy to build and deploy as software.