Prior Labs

Tables power financial models, clinical trials, and scientific experiments, but deep learning has mostly ignored tabular structure. Prior Labs built TabPFN, a foundation model that understands tabular data (published in Nature, 3M+ downloads). The company provides training infrastructure, real-time serving, and developer platform to deploy models in production. Hiring across product and research, including ML engineering, training infrastructure, ML platform full stack development, and research roles. Selected 20-person team with backgrounds from Jane Street, Google, CERN, G-Research; led by Frank Hutter, advised by Yann LeCun and Bernhard Schölkopf.