Research Scientist / Engineer - Dexterous Manipulation

At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for a Research Scientist or Research Engineer to advance dexterous manipulation — enabling our robots to perform contact-rich, fine-motor tasks that require precision, physical reasoning, and adaptability to novel objects and environments. What You'll Do - Research and develop learning-based approaches for dexterous and contact-rich manipulation tasks - Design training strategies and data collection protocols for fine-motor and multi-finger manipulation - Work on perception for manipulation: contact detection, tactile sensing, object pose estimation, and spatial reasoning - Build and evaluate policies that generalize to novel objects and unstructured environments - Develop simulation environments and benchmarks for dexterous manipulation research - Collaborate with robot hardware, perception, and learning teams to close the sim-to-real gap - Publish and present work at top-tier robotics and ML venues (especially valued for RS track) What We're Looking For - Strong background in robot learning, manipulation, or physical AI - Hands-on experience developing and evaluating manipulation policies on real hardware - Understanding of contact mechanics, grasp planning, or tactile sensing - Solid ML skills with experience in imitation learning, RL, or diffusion-based policies - Ability to work across the stack from simulation to real robot deployment Nice to Have (But Not Required) - PhD in Robotics, ML, or a related field - Publication record at ICRA, CoRL, RSS, NeurIPS, or related venues - Prior work on dexterous hands, multi-finger manipulation, or contact-rich tasks - Experience with tactile sensors or force/torque feedback in robot learning - Familiarity with simulation tools for manipulation (MuJoCo, Isaac Sim, Genesis) - Experience with skill libraries, language-conditioned manipulation, or task parameterization Why This Role - Push the frontier on one of the hardest open problems in robotics - Work with hardware and data resources that few research labs have access to - Direct path from research results to deployment on our humanoid platform - Tight collaboration across robot learning, hardware, and systems teams