Research Evaluation Analyst

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.