Staff ML Engineer

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 Impact: We aim to be the world-leading organization working on structured data. Our TabPFN v2 model, recently published in Nature, sets the new state-of-the-art for small structured data. Our models have gained significant traction with 1M+ downloads and 2,500+ GitHub stars. We are now building the next generation of models that combine AI advancements with specialized architectures for structured data.

Backing and Momentum: With €9M in pre-seed funding from top-tier investors including Balderton Capital, XTX Ventures, and Hector Foundation—and support from leaders at Hugging Face, DeepMind, and Silo AI—we’re moving rapidly toward commercialization.

Core Areas of Impact

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

What We're Looking For

• 5+ years industry experience in machine learning, software development or related field

• 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

What Sets You Apart

• 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

Location & Work Style

• Headquartered in Freiburg, Germany - a university city at the edge of the Black Forest, Switzerland and France, and office in Berlin

• Opening London in 2025

We're building a team that combines technical excellence with our core principles:

1. High-performing empathy - We deliver exceptional results while supporting and respecting each other

2. Undogmatic problem-solving - We value practical solutions over rigid principles

3. Positive impact - We integrate ethical considerations into everything we build

4. Product driven - We're driven to create breakthrough tools that transform how people work with data

Benefits

• 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