Account Executive, New York

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 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. 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 Clear path into sales leadership as the team scales Location This role is specifically located in our New York office 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.

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