Full Stack Engineer, ML Platform

WHO WE ARE Foundation models have transformed text and images, but structured data - the largest and most consequential data modality in the world - has remained untouched. Tables power every clinical trial, every financial model, every scientific experiment, every business decision. No one has built a foundation model that truly understands them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening - and we're hiring the team that makes it. Momentum: We pioneered tabular foundation models and are now the world-leading organization in structured data ML. Our TabPFN v2 model was published in Nature https://www.nature.com/articles/s41586-024-08328-6 and set a new state-of-the-art for tabular machine learning. Since its release, we've scaled model capabilities more than 20x, reached 3M+ downloads, 6,000+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics https://www.oxcan.org/news/prior-labs-and-oxford-cancer-analytics-partner-to-advance-liquid-biopsy-and-clinical-decision-making-in-lung-disease to preventing train failures with Hitachi https://siliconangle.com/2025/12/01/prior-labs-debuts-tabular-ai-foundation-model-scales-10-million-rows/ to improving clinical trial decisions with BostonGene https://priorlabs.ai/case-studies/boston-gene. The hardest work is in front of us. We're scaling tabular foundation models to handle millions of rows, thousands of features, real-time inference, and entirely new data modalities - while building the infrastructure to deploy them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team: We’re a small, highly selective team https://priorlabs.ai/about of 20+ engineers, researchers and GTM specialists, selected from over 5,000 applicants, with backgrounds spanning Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN, led by Frank Hutter https://www.linkedin.com/in/frank-hutter-9190b24b/, Noah Hollmann https://www.linkedin.com/in/noah-hollmann-668b9010b/ and Sauraj Gambhir https://www.linkedin.com/in/sauraj-g/ and advised by world-leading AI researchers such as Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, create top-tier research, and hold each other to an extremely high bar. What’s Next: In 2025, we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here which makes this an optimal time to join. ABOUT THE ROLE We’re looking for exceptional engineers to help build the ML Platform that powers our tabular foundation model line. This is a unique chance to work at the intersection of data science, agents, UX, and real-world economic impact. You'll work on the product end-to-end: frontend, backend, and everything in between. What you'll work on: - Build the core platform that puts tabular foundation models into users' hands — from data upload and exploration through inference and results - Architect reliable, low-latency backend services that handle real-time model inference at scale - Work directly with the research team to turn new model capabilities into production features - Own the frontend experience for technical users (data scientists, ML engineers) who have high expectations and low tolerance for friction You may be a good fit if you have: - 3+ years building highly-available, user-facing products across the full stack, with real ownership of what shipped - Experience building data-intensive applications (dashboards, analytics tools, data exploration interfaces, or similar) - Strong JavaScript/TypeScript and Python — you're genuinely good at both, not just passable in one - Good product instincts — you think about what the user actually needs, not just what the ticket says - Comfort working close to ML systems, even if you're