Research Intern, PhD (AI, Robotics)

We are an early-stage robotics startup working on building multi-purpose mobile robots that can do complex manipulation tasks. We are looking for a creative, skilled, and motivated research interns to advance robot manipulation capabilities. We are looking for people with proven expertise in machine learning and/or robotics. You will collaborate with a team of talented researchers and engineers, and drive ongoing innovation and technological advancements within the company. This is a full-time on-site role in Santa Clara, CA.ResponsibilitiesDevelop 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.QualificationsCurrently 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.

Created: 2026-04-02