Research Member of Technical Staff

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.

Responsibilities

• Design and implement RL training pipelines to improve robot policy performance
• Develop and apply RL algorithms (PPO, GRPO, or similar) adapted to video prediction
• Design and implement post-training pipelines including supervised fine-tuning and preference optimization
• Work on inverse dynamics models to translate video predictions into executable actions
• Build evaluation frameworks for post-trained policies on real hardware
• Research methods for efficient model adaptation with minimal demonstration data
• Iterate quickly between simulation and real robot evaluation
• Collaborate with pre-training teams to address model capability gaps

Requirements

• Hands-on experience with robot systems, robotic policy learning, or autonomous systems
• Strong understanding of imitation learning and reinforcement learning
• Practical familiarity with real robot hardware and sensor modalities
• Solid ML skills with hands-on PyTorch experience
• Ability to diagnose policy failures and reason about distribution shift

Preferred Qualifications

• Experience with reinforcement learning applied to real or near-real environments
• Prior industry experience in robotics, autonomous driving, or physical AI
• Experience with teleoperation systems or large-scale demonstration collection
• Familiarity with ROS/ROS2 and real-time control systems
• Experience with simulation environments like MuJoCo, Isaac Sim, or Genesis
• PhD in Robotics, ML, or a related field
• Publication record at ICRA, CoRL, RSS, or NeurIPS