ML Engineer, Foundation Model

Who We Are: Prior Labs is building breakthrough foundation models that understand spreadsheets and databases - the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We're tackling this $100B+ opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence.

Our Momentum: We're the world-leading organization working on structured data, and we're accelerating fast. Our TabPFN v2 model, recently published in Nature, sets the new state-of-the-art for structured data. We've hit 2.2M+ downloads, 5,000+ GitHub stars, and growth is accelerating. We're now building the next generation of models that combine AI advancements with specialized architectures for structured data.

What's Next: With €9M in pre-seed funding from top-tier investors and backing from leaders at Hugging Face, DeepMind, and Silo AI, we're scaling fast and building our team. This is the moment to join: help us shape the future of structured data AI. Read our manifesto.

You'll be among the engineers developing an entirely new class of AI models. Our latest breakthrough (TabPFN) outperforms all existing approaches by orders of magnitude - and we're just getting started. This is a rare opportunity to:

• Work on fundamental breakthroughs in AI, not just incremental improvements

• Shape the future of how organizations worldwide work with their most valuable data

• Join at the perfect time: We just received significant funding (announcement coming soon), have strong early traction (100K+ downloads), and are scaling rapidly

As an early-stage startup working on foundation models for tabular data, we have several key areas where ML Engineers can make significant contributions. As an early team member, you'll have significant technical ownership and the opportunity to grow into a leadership position as we scale. While no single person needs to cover all these areas, these represent the types of challenges you might tackle based on your interests and expertise:

Model Engineering & Implementation

• Build and improve training pipelines for large-scale tabular foundation models

• Design modular architectures that support rapid experimentation

• Optimize training and inference performance

Research Infrastructure & Tooling

• Improve experiment tracking and evaluation systems

• Build efficient data processing pipelines for tabular data

• Maintain clean, documented codebases that the team can build upon

Production & Scale

• Design scalable serving architecture for our models

• Implement deployment pipelines

• Strong engineering fundamentals with excellent Python expertise

• Deep experience with ML frameworks, especially PyTorch, Scikit-Learn

• Proven track record of implementing and deploying ML systems

• Passion for writing clean, maintainable, and well-documented code

• Demonstrated interest in foundation models and their real-world applications

• Master's degree or PhD in Computer Science or related technical field

• Contributions to open-source projects in related fields

• Experience implementing large language models or foundation models

• Track record of implementing papers

• Background in ML infrastructure and tooling

• Experience with distributed training systems

• Offices in San Francisco, NYC, Berlin, and Freiburg, with flexibility to work across our locations

• Competitive compensation package in line with industry experience plus meaningful equity

• 30 days of paid vacation + public holidays

• Comprehensive benefits including healthcare, transportation, and fitness

• Work with state-of-the-art ML architecture, substantial compute resources and with a world-class team

• 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, disabilities, or any other traits that make you who you are.