Head of Partnerships

1 мес. назад

USAHeadOnsite

Lead and manage partnership initiatives for a company pioneering tabular foundation models in AI.

О компании

Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood 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 as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ 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 ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run 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 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter , Noah Hollmann , and Sauraj Gambhir , and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do 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 ideal time to join.

Обязанности

You'll own all of ' partnerships, across both the SAP and non-SAP books of work. You'll start as an individual contributor, building the playbook before growing your own team. On SAP, the goal is to direct our limited engineering capacity toward the highest value-add projects. On non-SAP, it's to qualify inbound leads and generate outbound ones, building long term win-win partnerships.
Bring every partnership under one owner. Consolidate our existing partner relationships and processes into a single, well-run portfolio with clear ownership.
Own the SAP relationship. Manage SAP stakeholders' technical requests and prioritise ' limited engineering capacity toward the highest value work, and work through SAP's structures to shape high-value initiatives into win-win commercial outcomes.
Develop non-SAP partnerships into new revenue channels. Generate, qualify, and prioritise leads with outsized upside for everyone involved.
Open the technology and reseller ecosystem. Sign and run integration, co-marketing, and reseller partnerships across the ML and data stack (MLOps platforms, feature stores, data platforms, systems integrators).
Build the partner engine from scratch. Create the playbooks, co-sell and deal-registration processes, and enablement materials that let partners sell with minimal hand-holding.

Требования

You have built a partnerships or alliances motion from scratch as an individual contributor, sourcing, structuring, and closing partner-driven deals before there was a team or a playbook.
You have owned a strategic alliance with a large enterprise software vendor or global systems integrator and turned that single relationship into a repeatable, forecastable pipeline channel.
You understand how a large vendor's partner organization works: co-sell incentives, joint business plans, marketplace mechanics, and what actually motivates a partner's sales force to carry your product.
You can build a joint business plan, translate it into a time-bound pipeline plan, and report partner-sourced pipeline in a clear monthly cadence.
You are comfortable creating structure in an early-stage company, where there is ambiguity and no inherited process.

Будет плюсом

Cloud marketplace and co-sell experience that produced real revenue.
Integration or reseller partnerships across ML, data, or developer-infrastructure tooling.
Experience selling or partnering into the data science and ML engineering buyer.
Having operated through a company's acquisition by, or deep integration with, a large strategic acquirer.
Life at 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. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in excepti

Другое

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.