Research Scientist​/Engineer - 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 $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 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.

• 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)

• 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

• 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

• 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