Robot Learning Engineer

Responsibilities

• Design and implement state-of-the-art learning algorithms for robot manipulation, navigation, and control from simulation to deployment
• Develop novel approaches to enhance robot dexterity and mobility using reinforcement learning, imitation learning, and foundation models
• Scale ML systems for large-scale model training and fine-tuning
• Build diverse, robust manipulation skills to push the boundaries of robotic capabilities
• Collaborate closely with hardware, controls, and systems engineers to create integrated solutions

Requirements

• PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or related field; OR Master's with 1+ years industry experience; OR Bachelor's with 3+ years industry experience
• 2+ years of hands-on experience developing AI systems for robotics applications
• Deep expertise in modern robot learning techniques including reinforcement learning, imitation learning, and behavior cloning
• Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Proven experience conducting real robot experiments and debugging complex robotic systems
• Experience with robot simulators like Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, or Drake

Preferred Qualifications

• Publications at top robotics/ML conferences such as RSS, CoRL, ICRA, IROS, NeurIPS, or ICLR
• Experience with vision-language models or foundation models for robotics
• Familiarity with sim-to-real transfer techniques and domain randomization
• Experience with distributed training and MLOps infrastructure
• Background in manipulation, grasping, or mobile manipulation
• Track record of taking research from prototype to production

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.