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XDOF

Data pipelines and annotation for robotics

Member of Technical Staff - Vision / Language Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Mateo, CA, USAHybrid

About the Job

Requirements

  • A Master of Science or PhD in Computer Science, Robotics, Machine Learning, or a related field from a top-tier program.
  • Three to seven years of research or applied research experience in industry or academia in one or more of vision-language models, video understanding, robot learning, or generative modeling.
  • Deep fluency in PyTorch and working knowledge of large-scale training infrastructure, including distributed training, mixed precision, and large-batch workflows.
  • Published work or demonstrable impact in vision-language models or vision-language-action models, video representation learning, imitation learning, or a closely related area.
  • Strong engineering fundamentals, including the ability to design clean systems rather than only run experiments.

Responsibilities

  • Design and implement vision-language pipelines for egocentric and teleoperation video, including 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 across vision-language-action models, video prediction, and world models.
  • Build and improve data curation systems that assess the quality, diversity, and coverage of large-scale robot demonstration datasets.
  • Work hands-on with bimanual and high-degree-of-freedom manipulation data, including real teleoperation footage and simulation-generated rollouts.
  • Collaborate directly with partner labs to define data requirements and connect data quality with downstream policy performance.
  • Track research in vision-language-action models, video foundation models, flow matching, diffusion transformer architectures, and egocentric pretraining, and translate insights into production systems.

Desired Qualifications

  • Junior candidates will also be considered.

About the Company

XDOF

Data pipelines and annotation for robotics

XDOF builds data pipelines, data-collection tools, and annotation systems that frontier AI labs and robotics companies use to train robots to operate in the physical world. It tackles the data bottleneck in physical AI by combining teleoperation, simulation, and egocentric data collection, then layering in data cleaning, tooling, and annotation to prepare usable datasets. The company differentiates itself through its end-to-end data infrastructure for physical AI, its mix of teleoperation, simulation, and first-person data methods, and its Berkeley-founded background from 2024. Its goal is to enable robots to learn to operate in the real world by providing the pipelines and labels needed for training.

Company size
1-10
Company stage
Series A
Total funding
$78.3M
Headquarters
Berkeley, CA
Founded
2024

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