Rhoda AI

Research Member of Technical Staff- Post-training & Robot Learning

Mountain View · Staff+

Sponsorship not specifiedDetected 64 days ago

AlgorithmsMachine LearningPyTorchRoboticsHardware DesignControlsResearch

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.

Develop and apply RL algorithms (PPO, GRPO, or similar) adapted to the video prediction setting, including reward modeling and feedback collection strategies for physical task performance
Design and implement broader post-training pipelines: supervised fine-tuning, preference optimization, and behavioral alignment on robot-collected demonstration data
Build evaluation frameworks for post-trained policies: task success, generalization to novel objects and environments, and failure mode analysis on real hardware
Identify failure modes and systematic weaknesses in deployed robot policies and drive targeted improvements
Collaborate with the pre-training team to surface what capabilities are missing from the base model and need to be addressed upstream
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.
Staff-level candidates are expected to define technical direction and drive research strategy independently; senior candidates execute complex projects with strong fundamentals and growing scope
Your work is what makes our robots actually perform tasks reliably in the real world - the direct connection between pre-trained capability and deployed behavior

Solid ML skills with hands-on PyTorch experience
Ability to diagnose policy failures, reason about distribution shift, and iterate effectively on data and training strategies
Comfort with ambiguity and fast-changing research priorities
Prior industry experience in robotics, autonomous driving, or physical AI (e.g., manipulation, mobile robotics, self-driving stacks)
Experience with teleoperation systems or robot demonstration collection at scale
Familiarity with robot middleware (ROS/ROS2) and real-time control systems
Experience with simulation environments for robotics (MuJoCo, Isaac Sim, Genesis)
High ownership on a small team where robotics domain expertise is core to the mission

Iterate quickly between simulation and real robot evaluation to close the feedback loop

Practical familiarity with real robot hardware, deployment constraints, and sensor modalities (vision, proprioception)
Design and implement RL training pipelines to improve robot policy performance beyond what imitation learning alone achieves - reward design, online data collection, and policy optimization
Strong understanding of robot policy learning: imitation learning, behavior cloning, and how RL builds on top of it

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 with deep robotics or autonomous systems domain knowledge to adapt our web-pretrained video model to real robot tasks.

This listing is sourced directly from Rhoda AI's careers page and normalized into a canonical job model.