Who we are

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.

About the Role

We are hiring our first Account Executive to drive commercial adoption of our foundation models for structured data. This is a founding role — you'll shape how we sell, who we sell to, and what good looks like for every AE who joins after you. You'll own the full sales cycle across enterprise and mid-market accounts, working directly with the commercial founder and a team of ex-DeepMind, Palantir, Jane Street, Goldman Sachs and Amazon researchers and operators.

This role combines a strong outbound focus with the potential for end-to-end deal ownership. You'll spend most of your time on outreach and discovery with technical buyers (data scientists, ML engineers, technical leaders), while also navigating buying committees, developing proposals, and closing deals. You'll help create the materials and messaging that make our outbound motion successful while driving revenue outcomes. We're looking for someone who loves the craft of outbound and wants to build the engine, not just close deals.

Outbound and Pipeline Generation

Drive outbound outreach to high-potential accounts through email, LinkedIn, and community channels

Execute targeted campaigns and iterate based on what works

Qualify inbound leads and identify opportunities worth pursuing

Sales Cycle Ownership

Run discovery calls and product demos with data science and ML teams

Develop proposals and business cases tailored to customer needs

Navigate buying committees across technical and business stakeholders

Own opportunities from qualification through signed contract

Technical Engagement

Understand our product deeply and speak credibly with data scientists and ML engineers

Communicate technical value in a clear and compelling way

Shape tailored messages and outreach sequences for technical personas

Building the Motion

Help define qualification criteria, outbound sequences, demo structure, and objection handling - the playbook you help write is what we hire against next

Bring field intelligence back to the team on objections, positioning, and what customers actually care about

What you bring

3+ years in a full-cycle AE role at a data infrastructure, ML tooling, developer tools, or deep tech company

Track record closing enterprise and mid-market deals with technical buyers — data scientists, ML engineers, or engineering leadership

Strong technical literacy - comfortable holding a credible conversation with an ML team

Proven outbound execution and pipeline generation from scratch

Builder mentality - you want to figure out how to sell this, not inherit someone else's playbook

Bonus: hands-on experience with data science or ML workflows, or background selling to ML platform teams

Why this role is exciting

First AE at a company with real research credibility, a Nature publication, and production customers with the world's largest enterprises

Direct line to founders - you'll shape commercial strategy, not just execute it

Genuine category creation and bringing frontier AI to industry