Research Scientist / Engineer - Robot Learning Data
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Role details
Tech stack
Job description
- 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, * 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
Requirements
Do you have experience in System design?, * 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
About the company
At Rhoda AI, we’re building the full-stack foundation for the next generation of humanoid robots - from high-performance, software-defined hardware to the foundational models and video world models that control it. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling scenarios unseen in training. We work at the intersection of large-scale learning, robotics, and systems, with a research team that includes researchers from Stanford, Berkeley, Harvard, and beyond. We’re not building a feature; we’re building a new computing platform for physical work - and with over $400M raised, we’re investing aggressively in the R&D, hardware development, and manufacturing scale-up to make that a reality.
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