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 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 to preventing train failures with Hitachi to improving clinical trial decisions with BostonGene.
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 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, Noah Hollmann and Sauraj Gambhir 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.
Core Areas of ImpactIn this role you will do more than deploy models—you'll be instrumental in delivering transformative solutions that redefine how organizations harness data. Your role will be at the intersection of cutting-edge AI technology and real-world applications, working directly with our most strategic partners.
What You'll Do:
Customer Success & Deployment: Work hands-on with clients to deploy models, ensuring they achieve tangible business outcomes and measurable impact.
Integration Engineering: Design and implement seamless integrations with platforms like Databricks, Snowflake, and complex enterprise ecosystems.
Tailored AI Solutions: Customize and optimize models for diverse use cases, balancing performance, scalability, and business needs.
Product Feedback Loop: Gather insights from customer deployments to inform and influence product development, shaping the evolution of our models.
Cross-Functional Collaboration: Partner with ML researchers, product managers, and engineers to translate groundbreaking research into scalable, production-ready solutions.
Strong engineering fundamentals with expert-level Python skills
Hands-on experience with ML frameworks, particularly PyTorch and Scikit-learn
Proven track record of deploying ML systems in production environments
Strategic problem-solving mindset with a strong focus on customer outcomes
Commitment to writing clean, maintainable, and well-documented code
Bonus Points:
Experience in forward-deployed engineering or technical customer-facing roles
Contributions to open-source projects in ML or data engineering
Proficiency with cloud platforms (AWS, GCP, Azure) and modern data pipelines
Expertise in APIs, deployment pipelines, and enterprise integration architectures
Strong communication skills to engage both technical and business stakeholders
Life at Prior Labs
We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with.
We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you.
Our Commitments
We 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, disability, or any other trait that makes you who you are.
We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.
Skills Required
- Expert-level Python skills
- Experience with ML frameworks, particularly PyTorch and Scikit-learn
- Proven track record of deploying ML systems in production environments
- Experience with Databricks, Snowflake, or other enterprise data platforms
- Commitment to writing clean, maintainable, and well-documented code
What We Do
Prior Labs is building breakthrough foundation models that understand spreadsheets and databases - the lifeblood of science and business. While foundation models have transformed text and images, tabular data has remained largely untouched. We're tackling this opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence. Backed by Balderton Capital, XTX Ventures, SAP Founder Hans Werner-Hector's Hector Foundation, Atlantic Labs, Galion.exe and top AI leaders such as Peter Sarlin, Guy Podjarny, Thomas Wolf, Ed Grefenstette, Robin Rombach, Christopher Lynch and Ash Kulkarni.
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