Research Scientist / Engineer - Robot Learning Data

Rhoda Ai
Palo Alto, US
On-site

Who this role is best for

Best suited to mid-level research engineers with hands-on robotics experience working in Palo Alto at the intersection of data collection and model training.

Best fit for

  • Engineers who have built teleoperation systems for robot learning data.
    — “Hands-on experience with robotic data collection, teleoperation systems
  • Candidates capable of translating model needs into data strategies.
    — “translate model data needs into concrete collection strategies
  • Researchers with a track record of working with real robotic hardware.
    — “Experience working with real robotic hardware

Things to consider

  • The role requires direct collaboration with both hardware and research teams.
    — “Work across hardware, systems, and research
  • Data quality decisions will have compounding effects on all model training.
    — “improvements to data quality compound across every training run

How to stand out

  • Demonstrate specific examples of data curation pipelines you've built.
    — “Develop data quality metrics, curation pipelines
  • Highlight any experience with sim-to-real transfer methods.
    — “Experience with sim-to-real transfer
  • Showcase projects where you measured data impact on model performance.
    — “Measure the downstream impact of data collection decisions
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • developed high-quality robot learning data systems
  • improved model performance through data quality
Typical background
PhD in robotics or MLexperience in data collection and processing

Skills & requirements

Required

Robotic Data CollectionTeleoperation SystemsData Quality MetricsSoftware EngineeringHardware InteractionModel Performance Measurement

Preferred

Sim-to-real TransferSynthetic Data GenerationCross-embodiment DatasetsVR TeleoperationImitation Learning

Stack & domain

Robotic Data CollectionTeleoperation SystemsDemonstration FrameworksData Quality MetricsCuration PipelinesFiltering StrategiesRobotic Interaction DataSoftware EngineeringHardwarePipelinesModel PerformanceSim-to-real TransferSynthetic Data GenerationCross-embodiment DatasetsVr TeleoperationMotion CaptureDexterous Demonstration CollectionImitation LearningPolicy GeneralizationCollaborationProblem-solvingCommunicationLeadershipRoboticsData CollectionResearchAIMachine Learning

About the role

Original posting from Rhoda Ai via Ashby

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

Source: Rhoda Ai careers (Ashby)

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