Full Stack Engineer, ML Platform

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, We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with.

We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you.

We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together.

Our Commitments

We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box."

We're committed to creating a safe, inclusive environment and providing 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. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.

• 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)

Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood 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 as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run 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 of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do 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 ideal time to join.