Member of Technical Staff, Vision / Language

XDOF
  • San Francisco, California
    30+ days ago

    Job Description

    About XDOF

    Frontier labs are racing to build general-purpose robots, and the bottleneck isn't compute. It's data. At XDOF, we're building the foundation behind the foundation models: the data collection systems, annotation pipelines, exabyte-scale data infrastructure, and software toolchain that enable our partners to push the field forward.

    We're hiring a Research Engineer / Scientist to help lead technical efforts at the intersection of vision-language models and robot learning. You will build systems that turn raw egocentric and teleoperation video into high-signal training data for VLA models, and increasingly, contribute to the models themselves.

    Beyond pipelines, you will drive research into what makes robot data useful: discovering new metadata (contact events, affordance labels, implicit reward signals, dynamics priors from video) that unlock capabilities current approaches miss. You'll explore how structured annotations can improve cross-embodiment transfer, automatic curriculum generation, and world models that predict what actually matters for manipulation. The data layer isn't downstream of the research. It is the research.

    What You'll Do

    • Design and implement vision-language pipelines for egocentric and teleoperation video: structured captioning, temporal grounding, action-conditioned scene understanding, and semantic annotation at scale

    • Develop and evaluate representations that bridge visual perception, language, and low-level robot action — spanning VLAs, video prediction, and world models

    • Build and improve data curation systems that assess quality, diversity, and coverage of large-scale robot demonstration datasets

    • Work hands-on with bimanual and high-DoF manipulation data, including real teleoperation footage and sim-generated rollouts

    • Collaborate directly with partner labs to define data requirements and close the loop between data quality and downstream policy performance

    • Stay current on the research frontier (VLAs, video foundation models, flow matching, DiT architectures, egocentric pretraining) and translate insights into production systems

    Required:

    • MS or PhD in Computer Science, Robotics, Machine Learning, or a related field from a top-tier program

    • 3–7 years of research or applied research experience (industry or academic) in one or more of: vision-language models, video understanding, robot learning, or generative modeling

    • Deep fluency in PyTorch; working knowledge of large-scale training infrastructure (distributed training, mixed precision, large batch workflows)

    • Published work or demonstrable impact in VLMs/VLAs, video representation learning, imitation learning, or a closely related area

    • Strong engineering fundamentals — you can design clean systems, not just run experiments

    Benefits

    • Competitive compensation and equity

    • Comprehensive health and wellness benefits

    • Flexible work arrangements

    • Collaborative and fast-paced work environment

    • Opportunity to shape the future of robotics and AI alongside an ambitious, values-driven team

    Level: Mid Level to Senior Research Scientist (L4–L5 equivalent) Location: San Mateo

    Note: Junior candidates will still be considered

    If you’re excited to help build the infrastructure powering tomorrow’s intelligent machines, we’d love to hear from you!

    Numbers & Facts

    LocationSan Francisco, California

    Skills

    • Computer Scienceunmatched
    • Data Collectionunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Diversityunmatched
    • Infrastructure Softwareunmatched
    • Machine Learningunmatched
    • Metadataunmatched
    • Modeling Languagesunmatched
    • Predictive Modelingunmatched
    • Requirements Managementunmatched
    • Roboticsunmatched
    • Scene Understandingunmatched
    • Scientific Researchunmatched
    • Systems Analysisunmatched
    • Team Playerunmatched
    • Technical Leadershipunmatched
    • Technical Recruitingunmatched

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