Full Stack Engineer, ML Platform

Role Summary

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.

Responsibilities

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

Requirements

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)

About the Company

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.

LIFE AT PRIOR LABS

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.

OUR COMMITMENTS

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.

We care about how your data is handled - see our Recruiting Data Privacy https://priorlabs.ai/recruiting-data-privacy page