Research Scientist @ Prior Labs

Join Prior Labs!Who We Are: Prior Labs is 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.Read more about our vision on our blog.About the RoleYou'll be among the first 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 improvementsShape the future of how organizations worldwide work with their most valuable dataJoin at the perfect time: We just received significant funding, have strong early traction, and are scaling rapidlyWe'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 performanceBuilding multimodal models that combine text and tabular understandingDeveloping specialized architectures for time series, forecasting, and anomaly detectionCreating efficient inference methods for production deploymentResearching causal understanding in foundation modelsDesigning novel approaches for handling multiple related tablesQualificationsPhD in Computer Science, Applied Mathematics, Statistics, Electrical Engineering,…

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