Research Evaluation Analyst
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About this role
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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.
Mission
Support Research with high-quality, reliable robot experiments and data collection. Turn research needs into well-executed experiments, consistent operations, and trusted data that enable fast iteration.
Responsibilities
- Translate research needs into clear experiment plans, operating procedures, and data collection protocols.
- Support researchers with robot data collection, including task setup, scene/object preparation, pilot execution, and data QA.
- Own experiment execution end-to-end: model or task handoff → station readiness → execution → QA → results/data delivery.
- Train and coordinate research operations pilots; ensure consistency across people, shifts, and stations.
- Identify and troubleshoot issues related to hardware, setup, operators, data quality, and experiment execution.
- Maintain robot stations, resets, randomization, metadata, and experiment traceability.
- Track data quality, throughput, and operational bottlenecks; continuously improve research workflows.
- Partner closely with Research, Robot Data, and platform/infrastructure teams.
What We’re Looking For
- Some understanding of robotics, ML, or experimental workflows.
- Computer science, engineering, or other technical background; hands-on coding experience preferred.
- Rigorous and detail-oriented, with the ability to understand the intent behind an experiment rather than simply follow instructions.
- Strong hands-on execution, problem-solving, and ownership.
- Experience in robotics, data collection, lab operations, testing, or QA preferred.
Success Looks Like
Researchers can quickly hand off an experiment or data collection request and receive reliable execution, high-quality data, and well-documented results with minimal operational overhead.