Research Scientist - Tabular Foundation Models

Prior Labs GmbH; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Prior Labs GmbH, a frontier AI lab, is hiring researchers to advance foundation models for structured data, time series, and causal inference. You’ll develop models, design experiments, and publish results with the research team based between Berlin, Freiburg, and New York.

We welcome deep expertise in structured data or related areas, strong PyTorch skills, and a track record of original research. Remote work is possible in exceptional cases with travel to offices.

Qualifications

• A track record of original research contributions published in leading venues or notable open-source work.
• Strong experience developing and analyzing machine learning models with the ability to implement and debug methods in PyTorch.
• Solid understanding of training dynamics, generalization, and common failure modes in deep learning systems.
• Strong experimental judgment: choose solid baselines and distinguish robust improvements from artifacts.
• Excellent engineering fundamentals and strong Python skills with high-quality research code.

Responsibilities

• Develop models and learning methods that generalize across datasets and tasks.
• Identify worthwhile research questions, design experiments, and publish results and model releases.
• Implement and run experiments, interpret results, and collaborate with research engineers to turn ideas into reliable models.
• Contribute to the research agenda and help shape project direction.

Skills

PyTorch

Python

ML research

Job description

Prior Labs GmbH, a frontier AI lab, is hiring researchers to advance foundation models for structured data, time series, and causal inference. You’ll develop models, design experiments, and publish results with the research team based between Berlin, Freiburg, and New York.

We welcome deep expertise in structured data or related areas, strong PyTorch skills, and a track record of original research. Remote work is possible in exceptional cases with travel to offices.