Member of Technical Staff, Vision / Language

XDOF

San Mateo

On-site

PHP 9,452,000 - 11,972,000

Full time

33 hours ago
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Benefits offered by this job

Competitive compensation and equity
Comprehensive health and wellness
Flexible work arrangements
Collaborative environment
Shape future of robotics and AI

Job summary

XDOF is seeking a Research Engineer/Scientist to lead efforts at the intersection of vision-language models and robot learning. You will turn raw egocentric and teleoperation video into high-signal training data for VLA models and contribute to model development.

You will explore metadata and annotations to unlock capabilities across cross-embodiment transfer, curriculum generation, and world models, shaping data-driven robotics research into production systems.

Qualifications

  • MS or PhD in Computer Science, Robotics, Machine Learning, or related field from a top-tier program.
  • 3–7 years of research or applied research in vision-language models, video understanding, robot learning, or generative modeling.
  • Deep fluency in PyTorch and 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 related areas.
  • Strong engineering fundamentals — able to design clean, scalable systems.

Responsibilities

  • 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 bridging visual perception, language, and low-level robot action across 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 with partner labs to define data requirements and close the loop between data quality and downstream policy performance.
  • Stay current on the research frontier and translate insights into production systems.

Skills

Vision-language models
Video understanding
Robot learning
Generative modeling
PyTorch
Distributed training
Publications impact

Education

MS or PhD in CS/Robotics/ML

Tools

PyTorch

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.

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!

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