MLOps / ML Systems Engineer

Join Prior Labs!

Who We Are: Prior Labs is building tabular 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 $600B+ 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 was published in Nature and set the new state-of-the-art for structured data ML. Since it’s release, we’ve scaled up 20x in model capabilities, hit 2.5M+ downloads, 5,500+ GitHub stars, and growth is accelerating. We’re now building the next generation of models that combine AI advancements with specialized architectures for tabular data and actively commercializing them with global enterprises across Europe & the US.

The Team: We’re a small team of 20+ permanent hires selected from 5,000+ applicants - building the next generation of foundation models for structured data. Led by the founders behind the TabPFN lineage, we bring together talent from Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs and CERN, among others. We’re backed by heavyweight advisors including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet the team here.

What’s Next: Backed by top-tier investors and leaders from Hugging Face, DeepMind, Black Forest Labs and Silo AI, we’re scaling fast. This is the moment to join: help us shape the future of structured data AI. Read our manifesto.

About the role

You’ll take on challenging engineering tasks crucial to the development of tabular foundation models. You’ll work on building and maintaining best-in-class training infrastructure, while maintaining our developer productivity tooling and open source projects. You’ll work closely with researchers to ensure that we can iterate quickly and scale our models.

This is a rare opportunity to:

• Contribute to high-impact AI systems that are changing an industry

• Have significant impact by owning big projects from the start

• Join a world-class team at the perfect time: significant funding secured, strong early traction, and rapid scaling.

Key Responsibilities

• Training & research compute infrastructure: Own our cloud GPU cluster (operations, reliability, and cost/performance) currently based on Slurm. Design and implement future versions as our compute needs scale and we expand across multiple cloud/HPC providers.

• Training & inference performance: Work closely with researchers to identify and resolve performance bottlenecks in distributed training and inference. Support high hardware utilization and efficient memory usage through systems-level debugging, profiling, and infrastructure improvements.

• Developer productivity: Manage our internal repositories on GitHub and keep their CI and other pipelines speedy. Ensure our experiment tracking, model registry, data processing pipelines are working smoothly.

• Try out your own ideas! We operate an open environment. If you’ve got the next SOTA tabular architecture up your sleeve, go ahead and train it.

What we use today: Slurm, GCP, Docker, wandb, GitHub Actions, uv, Torch, Triton

Qualifications

• Exceptional software engineering fundamentals and expert-level Python proficiency, with 5+ years of hands-on industry experience building and operating production systems.

• Proven track record of designing and building complex, scalable software, preferably for data processing or distributed systems.

• Deep, practical knowledge of the modern ML ecosystem (PyTorch, scikit-learn, etc.) and a genuine interest in applying systems thinking to solve hard problems in AI.

• Core MLOps Concepts: Strong understanding of the entire machine learning lifecycle (MLLC) from data ingestion and preparation to model deployment, monitoring, and retraining. Familiarity with MLOps principles and best practices (e.g., reproducibility, versioning, automation, continuous integration/delivery for ML).

Location

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

Benefits

• Competitive compensation package with 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

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