ML Engineer at Prior Labs
Prior Labs is a VC-backed deep tech startup that grew out of the ELLIS ecosystem, with Frank Hutter and Bernhard Schölkopf among the co-founders. We're 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 3,500+ 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.
About the Role
We are building a world-leading diverse team of 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, have strong early traction, and are scaling rapidly
Next to this role, we are also hiring for all other roles: https://jobs.ashbyhq.com/prior-labs; please also feel free to encourage others to apply
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
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: we have offices in
Freiburg, Germany: a university city at the edge of the Black Forest, Switzerland and France
Berlin, Germany: a global tech hub and one of Europe’s most dynamic cities
At this point, we're hiring in-person roles only.
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
Timing of the job opening
We are hiring for multiple positions and will keep hiring, but the sooner the better
