Research Intern

Job Summary

We’re hiring Research Interns to train on the physical labor dataset. 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.

Key Responsibilities

• Run a research bet on Build data: train, evaluate, ablate, and write down what the data actually taught
• Work with researchers, dataset, and evals so the internship changes collection or evals, not only a slide
• Build the training and data path you need (PyTorch, dataset slices, evals) instead of waiting for a platform team
• Cover research and engineering. There is no intern track that is only notebooks

You May Be a Good Fit If You Have (Must-have Qualifications)

• Progress toward a Bachelor’s, Master’s, or PhD (preferred) in CS, EE, or a related field
• You have trained real models (course, lab, open source, or a paper). PyTorch or equivalent
• You want in-the-wild physical or video data, not only academic splits
• You can operate independently on a 12-week bet
• You will be in San Francisco, in person

Strong Candidates May Also Have Experience with

• Video, world models, robotics, or multimodal training
• Egocentric or in-the-wild video
• Large-scale training, dataset curation, or distributed GPU work
• Publication at a top conference (CVPR, NeurIPS, ICML, ICLR, RSS, CoRL, or equivalent)
• A paper, open-source model, or project that changed what you did next

Benefits

• Competitive pay
• 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 (Financial District) or Shenzhen (Nanshan)
• Various wellness benefits covering fitness, mental health, and more
• Daily lunch and dinner in our office
• Unlimited compute budget subject to ROI justification
• Unlimited Codex and Claude credits
• Travel

How We're Different

Build believes in the Bitter Lesson By taking a general approach of learning from humans, our addressable market is all physical labor.

We are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.