Research Scientist Intern

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 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.

About the role

You'll join the research team and work hands-on on an entirely new class of AI models. We have more open research problems than people to work on them, so you'll find challenges that match your interests and expertise. Problems we're working on:

• Scaling our transformer architectures from 10K to 1M+ samples while maintaining performance

• Building multimodal models that combine text and tabular understanding on proprietary data

• Developing specialized architectures for time series, forecasting, and anomaly detection

• Creating efficient inference methods for production deployment

• Researching causal understanding in foundation models