Research Scientist / Engineer - Robot Learning Data

Rhoda AI • Palo Alto, CA

4d

About The Position

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 possibly 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.

Requirements

• 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 Haves

• 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

Responsibilities

• 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

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed