Member of Technical Staff, Vision / Language

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 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

Additional Information

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.

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Company Intel

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