WHO WE ARE

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.

CORE AREAS OF IMPACT

A 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.

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 exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the

whole company comes together regularly for offsites to think, build, and celebrate together.

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.

Role

ML Engineer, Forward Deployed

Locations

New York

Published

June 25

Deadline

August 16

Tags for this job

Python AWS Azure GCP AI Machine Learning Rust

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