Member of Technical Staff, Vision / Language

xdof.ai; San Mateo (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation and equity

Comprehensive health and wellness benefits

Collaborative and fast-paced work environment

Job summary

xdof.ai in San Mateo is seeking a Mid Level to Senior Research Scientist to spearhead efforts in vision-language models and robot learning. This role involves designing innovative pipelines to transform video data into effective training data for advanced models, driving research to optimize robot data utility, and collaborating with partner labs to ensure data quality impacts policy performance.

The ideal candidate will possess an MS or PhD in a relevant field, offered in a dynamic environment with competitive compensation and health benefits.

Qualifications

• 3–7 years of research experience in vision-language models or related fields.
• Demonstrated impact in video representation learning or generative modeling.
• Ability to design clean systems beyond just running experiments.

Responsibilities

• Design vision-language pipelines for video data.
• Evaluate representations bridging visual perception and robot action.
• Collaborate with partner labs on data requirements.
• Stay current on related research to enhance production systems.

Skills

Fluency in PyTorch

Research experience in vision-language models

Knowledge of large-scale training infrastructure

Strong engineering fundamentals

Education

MS or PhD in Computer Science, Robotics, Machine Learning

Job description

Member of Technical Staff, Vision / Language

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

Competitive compensation and equity

Comprehensive health and wellness benefits

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!