Research Member of Technical Staff - Dexterous Manipulation

About the Company

Rhoda AI is 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. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up.

Responsibilities

• 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 including contact detection, tactile sensing, and object pose estimation
• 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

Requirements

• 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

Preferred Qualifications

• 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 like MuJoCo, Isaac Sim, or Genesis
• Experience with skill libraries, language-conditioned manipulation, or task parameterization