Prior Labs · Berlin
Software EngineeringEngineering & ScienceFullTimeposted 2mo ago
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 cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi. 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+ with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, 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 as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years.
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 not training models yourself — you understand model inputs, outputs, and failure modes well enough to build reliable interfaces around them
Enthusiasm for working in a fast-moving, ambiguous environment where new ideas ship quickly and user impact matters most
Bonus:
Cloud infrastructure experience (GCP preferred)
Background building developer tools, data platforms, or ML-adjacent products
Experience with React, FastAPI, and Postgres (our current stack)
You'll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other. We move fast and still take the time to do things right.
Our teams are based in Berlin, Freiburg, and New York - when you're working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we're open to remote, which usually means frequent travel to one of our offices. Wherever you're based, the whole company comes together regularly for offsites to build and celebrate together.
The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you've ever felt discouraged by "not checking every box" - and provide equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are.
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