Research Member of Technical Staff- Dexterous Manipulation
Rhoda AI · Mountain View, CA · 1 wk ago
On-siteEngineeringFull-time
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
- Able 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