Research Scientist / Engineer - Robot Learning Data

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 $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for a Research Scientist or Research Engineer to own the strategy and systems for collecting, curating, and scaling high-quality robot learning data. This role sits at the intersection of robotics, data collection, and research — your work directly determines the diversity and quality of the demonstrations our models train on. What You'll Do - Design and implement teleoperation and demonstration collection systems for high-quality robot learning data - Develop data quality metrics, curation pipelines, and filtering strategies specific to robotic interaction data - Research methods to augment real robot data with synthetic, simulated, or cross-embodiment sources - Identify and source external robotic datasets to expand training diversity across platforms and tasks - Build tooling for researchers to explore, annotate, and iterate on robotic datasets - Collaborate with pre-training and post-training teams to translate model data needs into concrete collection strategies - Measure the downstream impact of data collection decisions on model and policy performance What We're Looking For - Hands-on experience with robotic data collection, teleoperation systems, or demonstration frameworks - Understanding of what makes robot learning data useful: diversity, coverage, temporal quality, and action fidelity - Strong software engineering skills for building reliable data collection and processing systems - Ability to reason across hardware, pipelines, and model performance - Experience working with real robotic hardware in a research or industrial setting Nice to Have (But Not Required) - Experience with sim-to-real transfer and synthetic data generation for robotics - Familiarity with cross-embodiment datasets (e.g., Open X-Embodiment, DROID) - Experience with VR teleoperation, motion capture, or dexterous demonstration collection - Understanding of imitation learning and how data properties affect policy generalization - PhD or strong research background in robotics or ML Why This Role - The data you collect and curate is the direct upstream dependency for all model quality - Unique leverage: improvements to data quality compound across every training run - Work across hardware, systems, and research in a way few roles allow - Direct feedback loop with both robot operators and research scientists to continuously improve data quality