Research Intern

About Build AI Build AI is the data hyperscaler for Physical AI. We co-design hardware, collection, infrastructure, and research to scale the physical labor dataset orders of magnitude faster than anyone in the world.

Job Summary

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.

Key Responsibilities

Run a research bet on Build data: train, evaluate, ablate, and write down what the data actually taught Work with Members of Technical Staff, Head of Dataset & Quality, and Evals Lead 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 (Nice-to-have qualifications) 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 subsid