Research Member of Technical Staff- Reasoning

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 $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.

We're looking for Research Scientists and Research Engineers to advance the reasoning and planning capabilities of our foundation world models — enabling robots to decompose goals, plan multi-step actions, and handle long-horizon tasks in complex, unstructured environments. We hire across levels — from senior to staff.

What You'll Do

• Research and develop methods for multi-step reasoning and planning grounded in embodied world models

• Design architectures and training strategies that improve compositional generalization and long-horizon prediction

• Explore chain-of-thought reasoning, process reward models, and test-time search in the context of robotic control

• Build evaluation benchmarks for reasoning and planning capabilities applied to physical tasks

• Investigate how world model rollouts can enable planning and decision-making at inference time

• Collaborate with pre-training and post-training teams to integrate reasoning capabilities into the full model pipeline

• Publish and present work at top-tier venues (especially valued for RS track)

What We're Looking For

• Strong background in reasoning, planning, or search with large models

• Deep understanding of sequence modeling, transformer architectures, and generative models

• Experience with test-time compute methods (beam search, MCTS, self-consistency, verifiers, etc.)

• Strong research taste and ability to identify high-leverage directions

• Fluency with PyTorch or JAX and ability to implement and iterate on research ideas end-to-end

• Staff-level candidates are expected to define technical direction and drive research strategy independently; senior/MTS candidates execute complex projects with strong fundamentals and growing scope

• Nice to Have (But Not Required)

• PhD in ML, Robotics, or a closely related field

• Publication record at NeurIPS, ICML, ICLR, CoRL, or related venues

• Prior work on reasoning in LLMs (chain-of-thought, process reward models, search-based methods)

• Experience with model-based planning or hierarchical reinforcement learning

• Familiarity with long-horizon prediction, video generation, or world model rollouts

• Experience with embodied AI or robotic planning problems

• Why This Role

• Tackle one of the hardest open problems in embodied AI: enabling robots to reason about what to do next

• Research that directly translates to robot behavior in complex, real-world scenarios

• High research freedom grounded in real task performance

• Tight collaboration with pre-training, post-training, and robotics teams