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About the Role
We’re hiring Research Interns to train on the in-the-wild physical labor dataset. This is the intern version of Member of Technical Staff: you run a real research bet for about 12 weeks, not a toy project. Collection is monocular 1920×1080p 30fps, targeting 100M hours. If you have a bet on video, world models, or physical-labor data, you might as well run it here.
Responsibilities
- Run a research bet on Build data: train, evaluate, ablate, and document findings.
- Collaborate with technical staff, Head of Dataset & Quality, and Evals Lead to influence collection or evaluations.
- Develop necessary training and data paths (PyTorch, dataset slices, evals) independently.
- Engage in both research and engineering tasks; no notebook-only tracks.
Requirements
- Progress toward a Bachelor’s, Master’s, or PhD in CS, EE, or a related field.
- Experience training real models using PyTorch or equivalent.
- Interest in in-the-wild physical or video data, beyond academic splits.
- Ability to operate independently on a 12-week project.
- Must be in San Francisco, in person.
Skills
- PyTorch
- Video
- World models
- Robotics
- Multimodal training
- Egocentric video
- In-the-wild video
- Large-scale training
- Dataset curation
- Distributed GPU work
Location
- San Francisco, CA
- Shenzhen, China
Work Type
- In-person
- Internship
Experience Level
- Intern
Education Level
- Bachelor's degree
- Master's degree
- PhD
Salary/Compensations
- Competitive pay
Benefits
- Medical, dental, and vision packages with generous premium coverage
- $500 per month credit for waiving medical benefits
- Housing subsidy of $2k per month for those living within walking distance of the office
- Relocation support for those moving to San Francisco or Shenzhen
- Various wellness benefits covering fitness, mental health, and more
- Daily lunch and dinner in our office
- Unlimited compute budget subject to ROI justification
About the Company
- Build AI is the data hyperscaler for Physical AI, co-designing hardware, collection, infrastructure, and research to scale the physical labor dataset.
- Build believes in the Bitter Lesson and takes a general approach of learning from humans, with an addressable market of all physical labor.
- We are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), valuing engineering skills.
- We have no boundaries between engineering and research, expecting all technical staff to contribute to both and work across disciplines.
Equal Opportunity
- Build AI is an equal opportunity employer. We review every application. If you do not meet every bullet, still apply.