Research Intern, PhD (AI, Robotics)

Roboticsconnected; Fremont (CA); On-site; USD 40,000 - 60,000; Full time

Job summary

DEXMATE is seeking PhD research interns to advance robot learning on real hardware. You will develop new algorithms for dexterous manipulation, navigation, and control, and validate ideas on Dexmate robots with our research and engineering teams.

You will train and fine-tune large models, conduct multi-disciplinary research (robotics, RL/IL, perception, ML/DL), and design learning-based control systems using real robots with our team in California.

Qualifications

• PhD candidate in CS/Robotics/EE/ME or related field.
• 2+ years of independent research in robotics or AI.
• Experience with PyTorch and deep learning.
• Authorized to work in the U.S. during employment.
• Strong analytical, problem-solving, and communication skills.
• Publications in top conferences/journals preferred.

Responsibilities

• Develop algorithms for dexterous manipulation, navigation, and control.
• Train and fine-tune large models and validate on Dexmate robots.
• Collaborate with research and engineering teams.
• Coordinate experiments and analyze results on real hardware.
• Publish findings at conferences/journals when possible.

Skills

PhD in CS/Robotics/EE/ME

Robotics passion

Embodied AI research

PyTorch

US work authorization

Analytical & communication

Independent research (2+ yrs)

Robot learning (RL/IL)

Robot simulators (Isaac Gym/Sim, SAPI,

ML experiment setup and analysis

ML/DL systems building

Education

PhD candidate in CS/Robotics/EE/ME

Tools

PyTorch

Robot simulators

Job description

ABOUT DEXMATE

Dexmate is building the foundation for physical AI — combining a new generation of robots with a universal Physical AI OS, making robots as easy to build and deploy as software. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that. Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI.

If you want to help shape the next layer of human capability — and believe the future of robotics should be built together, not in isolation — we'd love to build it with you.

THE ROLE

We are looking for PhD research interns to push the frontier of robot learning on real hardware. You will develop new algorithms for dexterous manipulation, navigation, and control, train and fine-tune large models, and validate your ideas on Dexmate robots alongside our research and engineering teams.

RESPONSIBILITIES

• Develop new algorithms and methods for training AI models for enhancing the robot dexterity.
• Conduct cutting edge research across multiple disciplines (Robotics, RL/IL, control, perception, LLM, VLM, etc.).
• Work with large-scale ML systems and large-scale model training/fine-tuning.
• Design and implement state-of-the-art learning-based manipulation/navigation/control algorithms on real robots.
• Work with other teams to develop a diverse set of robust manipulation skills for robots.

MINIMUM QUALIFICATIONS

• Currently enrolled in a PhD degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, etc., or related technical field.
• Passionate about working with robots.
• Research experience in embodied AI, robotics, computer vision, machine learning, human-AI interaction, and computer science.
• Experience with deep learning frameworks such as PyTorch.
• Must obtain work authorization in U.S. at the time of hire and maintain ongoing work authorization during employment.
• Excellent analytical, problem-solving, and communication skills.
• At least 2 years of experience conducting independent research.
• Deep understanding of the SOTA robot learning techniques (reinforcement learning, imitation learning, etc.)
• A track record of research excellence with your work published in top conferences and journals such as Science Robotics, IJRR, RSS, CoRL, ICRA, NeurIPS, ICML, ICLR, CVPR, etc.
• Experienced with robot simulators such as Isaac Gym/ Isaac Sim/ SAPIEN/ MuJoCo/Drake, etc.
• Experience setting up ML experiments and analyze their results.
• Experience building systems based on machine learning and/or deep learning methods.