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Rhoda AI is seeking a detail-oriented operator to support researchers with robot experiments and data collection. You will translate research needs into clear experiment plans, set up tasks, and ensure reliable data collection across stations.
You will own end-to-end experiment execution from preparation to QA and results delivery, train pilots, and coordinate across teams to improve workflows.
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.
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.
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.
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.
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.