Who we arePrior Labs is building foundation models that understand tabular data, the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We're tackling this $600B opportunity to fundamentally change how organizations work with scientific, medical, financial, and business data.Momentum: We're the world-leading organization in structured data ML. Our TabPFN v2 model was published in Nature and set a new state-of-the-art for tabular machine learning. Since its release, we've scaled model capabilities more than 20x, reached 2.5M+ downloads, 5,500+ GitHub stars, and are seeing accelerating adoption across research and industry. We're now building the next generation of tabular foundation models and actively commercializing them with global enterprises across Europe and the US.Our team: We're a small, highly selective team of 20+ engineers and researchers, selected from over 5,000 applicants, with backgrounds spanning Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN, led by the creators of TabPFN and advised by world-leading AI researchers such as Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet the team here.What's Next: Backed by top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we're scaling fast. This is the moment to join: help us shape the future of structured data AI. Read our manifesto.Core Areas of ImpactYoull be among the engineers developing an entirely new class of AI models. Our latest breakthrough (TabPFN) outperforms all existing approaches by orders of magnitude - and were 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 (announcement coming soon!), have strong early traction (100K+ downloads), and are scaling rapidlyAt Prior Labs, we dont believe in "throwing research over the wall." Our Research Engineers are core members of the science team, contributing to architectural design while ensuring our models scale to the next order of magnitude. As an early team member, youll have significant technical ownership and the opportunity to grow into a leadership position as we scale. While no single person needs to cover all these areas, these represent the types of challenges you might tackle based on your interests and expertise:Model Engineering & ImplementationBuild and improve training pipelines for large-scale tabular foundation modelsDesign modular architectures that support rapid experimentationOptimize training and inference performanceResearch Infrastructure & ToolingImprove experiment tracking and evaluation systemsBuild efficient data processing pipelines for tabular dataMaintain clean, documented codebases that the team can build uponProduction & ScaleDesign scalable serving architecture for our modelsImplement deployment pipelinesWhat Were Looking ForStrong engineering fundamentals with excellent Python expertiseDeep experience with ML frameworks, especially PyTorch, Scikit-LearnProven track record of implementing and deploying ML systemsPassion for writing clean, maintainable, and well-documented codeDemonstrated interest in foundation models and their real-world applicationsWhat Sets You ApartMasters degree or PhD in Computer Science or related technical fieldContributions to open-source projects in related fieldsExperience implementing large language models or foundation modelsTrack record of implementing papersBackground in ML infrastructure and toolingExperience with distributed training systemsLocation Offices in Freiburg, Berlin, San Francisco and NYC, with flexibility to work across our locationsBenefitsCompetitive compensation package in line with industry experience plus meaningful equity30 days of paid vacation + public holidaysComprehensive benefits including healthcare, transportation, and fitnessWork with state-of-the-art ML architecture, substantial compute resources and with a world-class teamOur CommitmentsWe 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, disabilities, or any other traits that make you who you are.