Senior Technical Recruiter

WHO WE ARE Foundation models have transformed text and images, but structured data - the largest and most consequential data modality in the world - has remained untouched. Tables power every clinical trial, every financial model, every scientific experiment, every business decision. No one has built a foundation model that truly understands 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 in Nature https://www.nature.com/articles/s41586-024-08328-6 and set a new state-of-the-art for tabular machine learning. Since its release, we've scaled model capabilities more than 20x, reached 3M+ downloads, 6,000+ GitHub stars, and are seeing accelerating adoption across research and industry - 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/ to improving clinical trial decisions with BostonGene https://priorlabs.ai/case-studies/boston-gene. The hardest work is in front of us. We're scaling tabular foundation models to handle millions of rows, thousands of features, real-time inference, and entirely new data modalities - while building the infrastructure to deploy 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 https://priorlabs.ai/about of 20+ engineers, researchers and GTM specialists, selected from over 5,000 applicants, with backgrounds spanning Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, 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 world-leading AI researchers such as Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, create 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 optimal time to join. Your Responsibilities - Source scarce ML research and infra talent globally, exploring mainstream and niche talent pools - Position Prior Labs compellingly against other foundation model labs such as OpenAI, Anthropic, DeepMind, and Mistral - Navigate multi-hub hiring across Freiburg, Berlin, and New York (visas, comp bands, notice periods) - Screen technical depth quickly without burning founder time - Run efficient, structured interview loops with clear rubrics and fast debriefs - Manage, negotiate and close offers - Manage the pipeline operationally in the ATS with clean stages and weekly metrics The experience we are looking for - 5+ years in-house technical recruiting at a deep-tech, AI/ML, or research-led startup (seed to Series B) - Track record closing ML researchers or research engineers against top tier frontier labs (e.g. OpenAI, Anthropic, DeepMind, Mistral) - Hands-on hiring across at least two of: Germany, wider EU, and the US (NYC) The knowledge we expect you to already know - Fluency in the ML talent landscape: top labs, conferences, and what distinguishes a strong research vs. engineering vs infrastructure profile - Modern ATS architecture (Ashby or equivalent): stage design, rejection taxonomy, funnel reporting The skills you should bring to the role - Outbound sourcing on LinkedIn, GitHub, Google Scholar, and arXiv wit