Rhoda AI
Research Member of Technical Staff- Reasoning
Mountain View · Staff+
Sponsorship not specifiedDetected 65 days ago
Machine LearningPyTorchNLPLLMsRoboticsHardware DesignResearchCollaboration
About the role
- 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 hire across levels - from senior to staff.
Responsibilities
- 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
- Build evaluation benchmarks for reasoning and planning capabilities applied to physical tasks
- Collaborate with pre-training and post-training teams to integrate reasoning capabilities into the full model pipeline
- 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
- 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.
Requirements
- Experience with test-time compute methods (beam search, MCTS, self-consistency, verifiers, etc.)
- Strong research taste and ability to identify high-leverage directions
- Familiarity with long-horizon prediction, video generation, or world model rollouts
- Experience with embodied AI or robotic planning problems
Nice to have
- Nice to Have (But Not Required)
Company info
- What We're Looking For
- At Rhoda AI, we're building the next generation of generalist intelligent robots.
- 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.
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This listing is sourced directly from Rhoda AI's careers page and normalized into a canonical job model.