Member of Technical Staff

About Build AI Build AI is the data hyperscaler for Physical AI. We're vertically integrated across hardware, manufacturing, logistics, collection, and model training to scale the physical labor dataset orders of magnitude faster than anyone in the world. Job Summary We’re hiring Members of Technical Staff — the general research/engineering seat. If you have a seriously compelling research bet you want to run on physical-labor, video, or world-model data, you might as well do it at Build. We have the dataset, we are scaling it by orders of magnitude, and a small team that will actually let you train on it. You are not hired to polish a narrow job description. You are hired to pursue the bet, and to help us see what the data is teaching. Key Responsibilities Run research bets on Build data: train, evaluate, ablate, and ship what works Design and train models on in-the-wild video and physical-labor data; figure out what actually gets learned as we scale, and what is still missing Build the training and data paths you need (PyTorch, distributed training, dataset curation) instead of waiting for a platform team Work with Head of Dataset & Quality and Evals Lead so your results change collection and evals, not only a paper Cover research and engineering as needed in a team under 30 Design evaluation frameworks for your bets that are honest about generalization, not only a training curve You may be a good fit if you have (Must-have qualifications) You’ve trained real models. You have a research bet you could defend Proficiency in Python and a deep learning framework (PyTorch or equivalent) You want to work on in-the-wild physical data, not only academic splits You can move between research questions and engineering to get an experiment done Ability to operate independently on an ambiguous, high-impact direction Strong candidates may also have experience with (Nice-to-have qualifications) Video, world models, robotics, or multimodal training Experience with large-scale pretraining, dataset curation, or distributed GPU training Familiarity with egocentric / first-person or in-the-wild video Published work or shipped models that changed what a lab 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. Build AI is an equal opportunity employer. We review every application. If you do not meet every bullet, still apply. Questions: research@build.ai