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 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 Scholkopf 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 ImpactA model that tops a benchmark and a model that changes how an organization works are two different things. You'll take our tabular foundation models into our most strategic customers' environments - integrating them into real platforms and pipelines, doing the hands-on data science to prove value, and owning the implementation through to production.
This is a senior role: You'll own engagements end-to-end with high autonomy, make hard technical calls under ambiguity, and work shoulder-to-shoulder with customer data science teams as a senior peer. The patterns you uncover in the field won't stay in the field - they flow straight back to our researchers and shape what we build next. You won't just deploy models; you'll help shape how Prior Labs deploys as we scale.
What You'll Do:
Integrate: Embed our foundation models into customer platforms, cloud environments, and ML pipelines.
Do the Data Science: Frame the problem on real, messy data, engineer features, model it, and benchmark rigorously against the customer's current baseline.
Own Delivery: Carry use cases end-to-end - from first conversation to a reliable, documented production solution you stand behind.
Partner Deeply: Work with customer data science and ML teams as a peer, earn their trust, and make them faster with our models.
Tailor & Optimize: Customize models for diverse use cases, trading off performance, latency, scale, and cost.
Close the Loop: Turn deployment insights into sharp, prioritized feedback that shapes the model and product roadmap.
Set the Standard: Establish the deployment patterns the team builds on as we scale.
What We're Looking For:3+ years building and deploying ML systems in production, with a track record of owning hard problems end-to-end.
Strong engineering fundamentals and expert-level Python.
Deep, hands-on ML ability - you build models you understand and can defend, not just call an API. Strong with PyTorch and scikit-learn, with a solid grasp of transformer / foundation-model approaches.
Depth in tabular, time series, or structured-data ML.
Proven cloud deployment (AWS, GCP, or Azure) into production, kept reliable under real-world conditions.
Mature customer instinct - you diagnose the real problem, navigate technical and business stakeholders, and drive to outcomes.
High autonomy and sound judgment in ambiguity, and a bias toward clean, maintainable, well-documented code.
What sets you apart
Prior forward-deployed, solutions engineering, or senior technical customer-facing experience.
Contributions to relevant open-source projects in ML or data engineering.
Experience integrating with enterprise data ecosystems and designing APIs and deployment pipelines.
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.