Full Stack Engineer, ML Platform

About the role

WHO WE ARE

Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we're doing for tables.

We pioneered tabular foundation models: TabPFN v2 was a Nature https://www.nature.com/articles/s41586-024-08328-6 cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production 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/. The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level.

We're a small, highly selective team of 40+ https://priorlabs.ai/about with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, 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 Bernhard Schölkopf and Turing Award winner Yann LeCun.

In July 2026, less than 18 months after our €9M pre-seed, we joined SAP https://priorlabs.ai/blog-posts/priorlabs-sap as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years.

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