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Aufgaben

Most enterprises will never call our API directly. They will meet TabPFN inside the platforms they already run: SAP, AWS, Azure, Google Cloud, Databricks, or their own cloud. How well that works, how fast each release arrives there, and which platforms come next is the job of our Technical Product Manager for Integrations. You take each model release from handover to live across every channel, working with the engineers who build the model and the partner teams who host it. Inside SAP you carry the product side of TabPFN across its platforms, from AI Core to SAP Analytics Cloud, and you help build the integration engineering team that will work with you. Several decisions are yours to bring to the table: which announced channels we build next, what a marketplace listing should cost, how support for all of this works. You work directly with our product team, our engineers and the founders, and you report to the CTO. This suits someone who enjoys landing things on a date as much as deciding what to build, and who still likes being close to the code.

- Take every model release live across SAP, the cloud marketplaces and customer environments, on a plan you build with product and engineering. - Be the technical counterpart for the partner teams that host TabPFN, from SAP s platform teams to the hyperscaler marketplaces. - Shape how TabPFN shows up inside SAP s stack and what the integration engineering team builds first. - Bring the open channel decisions to the founders with a recommendation, and stay hands-on: listings, docs, smoke tests, a PR when it is faster than asking.

Anforderungen

Two or more years as product manager for a platform or integration surface: a product that ships into partners platforms, or that other companies build on. - You have shipped through gates you did not control, landed multi-team releases on dates, and made a large enterprise s process work for a small, fast team. - You started as an engineer and never fully stopped: you read code, logs and scan reports without a translator. - You are in Berlin or ready to relocate; Freiburg or New York can work. What sets you apart - You have shipped into an SAP, Salesforce, Microsoft or Oracle ecosystem, or know the cloud marketplaces from the inside. - You have deployed machine learning models and know what GPUs cost. - You have worked at a startup, and you use AI tools to take real work off your plate. Life at Prior Labs You ll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other.

We move fast and still take the time to do things right. Our teams are based in Berlin, Freiburg, and New York - when you re working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we re open to remote, which usually means frequent travel to one of our offices.

Wherever you re based, the whole company comes together regularly for offsites to build and celebrate together. Our Commitments The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you ve ever felt discouraged by not checking every box - and provide 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 - see our Recruiting Data Privacy page

Über das Unternehmen

Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we re doing for tables.

We pioneered tabular foundation models: TabPFN v2 was a Nature cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi. The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level. We re a small, highly selective team of 40+ with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by Bernhard Schölkopf and Turing Award winner Yann LeCun.

In July 2026, less than 18 months after our €9M pre-seed, we joined SAP as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years.