Research Scientist at Prior Labs, Freiburg or Berlin
Prior Labs is a VC-backed deep tech startup that grew out of the ELLIS ecosystem, with Frank Hutter and Bernhard Schölkopf among the co-founders. We're building breakthrough foundation models that understand spreadsheets and databases—the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We’re tackling this $100B+ opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence.
Our Impact: We aim to be the world-leading organization working on structured data. Our TabPFN v2 model, recently published in Nature, sets the new state-of-the-art for small structured data. Our models have gained significant traction with 1M+ downloads and 3,500+ GitHub stars. We are now building the next generation of models that combine AI advancements with specialized architectures for structured data.
Backing and Momentum: With €9M in pre-seed funding from top-tier investors including Balderton Capital, XTX Ventures, and Hector Foundation—and support from leaders at Hugging Face, DeepMind, and Silo AI—we’re moving rapidly toward commercialization.
About the Role
We are building a world-leading diverse team of scientists developing an entirely new class of AI models. Our latest breakthrough (TabPFN) outperforms all existing approaches by orders of magnitude, and we're just getting started. This is a rare opportunity to:
Work on fundamental breakthroughs in AI, not just incremental improvements
Shape the future of how organizations worldwide work with their most valuable data
Join at the perfect time: We just received significant funding, have strong early traction, and are scaling rapidly
Next to this role, we are also hiring for all other roles: https://jobs.ashbyhq.com/prior-labs; please also feel free to encourage others to apply
We're pushing the boundaries of what's possible with transformer architectures for structured data. Key challenges include:
Scaling our transformer architectures from 10K to 1M+ samples while maintaining performance
Building multimodal models that combine text and tabular understanding
Developing specialized architectures for time series, forecasting, and anomaly detection
Creating efficient inference methods for production deployment
Researching causal understanding in foundation models
Designing novel approaches for handling multiple related tables
Qualifications
PhD in Computer Science, Applied Mathematics, Statistics, Electrical Engineering, or a related field
Deep experience with ML frameworks, especially PyTorch and scikit-learn
Strong engineering fundamentals with excellent Python expertise
Experience in data-science and working with tabular data or time series
Publications at top-tier venues (NeurIPS, ICML, ICLR) or significant open-source contributions
Location: we have offices in
Freiburg, Germany: a university city at the edge of the Black Forest, Switzerland and France
Berlin, Germany: a global tech hub and one of Europe’s most dynamic cities
At this point, we're hiring in-person roles only.
Benefits
Competitive compensation package with meaningful equity
30 days of paid vacation + public holidays
Comprehensive benefits including healthcare, transportation, and fitness
Work with state-of-the-art ML architecture, substantial compute resources and with a world-class team
Timing of the job opening
We are hiring for multiple positions and will keep hiring, but the sooner the better
Apply by Dec 31st. Sooner applications are appreciated.
