Research Engineer: Tabular Foundation Models

Prior Labs GmbH; North Merrick (NY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Prior Labs GmbH seeks Research Engineers to advance TabPFN technology. You will design experiments, implement training pipelines, and contribute to papers while building scalable ML systems in an elite team. Offices in Europe and New York support collaboration, with remote work possible in exceptional cases.

You should have a Master’s or PhD in CS, strong Python/PyTorch skills, and published research. Experience with transformers or foundation models is preferred and a passion for efficient,

Qualifications

• Master's or PhD in Computer Science or related field.
• Publications at top ML venues or equivalent demonstrated research impact.
• Proficiency in Python, PyTorch, and ML ecosystem (scikit-learn, pandas, NumPy).
• Experience implementing and training neural network architectures, ideally transformers or foundation models.
• Understanding training dynamics, scaling behavior, and failure modes in DL systems.
• Interest in model efficiency and deployment-ready optimization.

Responsibilities

• Design experiments and ablations for TabPFN scaling and architectures.
• Contribute to papers and code that turn architectural ideas into trained models.
• Own training and evaluation infrastructure to enable rapid experimentation.
• Maintain high software quality alongside research deliverables.
• Collaborate with researchers and engineers across the team.

Skills

Research experience

Publications

Python

PyTorch

scikit-learn

Pandas

NumPy

ML systems

Training dynamics

Model efficiency

Education

Master's or PhD in Computer Science

Tools

Python

PyTorch

Scikit-learn

Pandas

NumPy

Job description

Prior Labs GmbH seeks Research Engineers to advance TabPFN technology. You will design experiments, implement training pipelines, and contribute to papers while building scalable ML systems in an elite team. Offices in Europe and New York support collaboration, with remote work possible in exceptional cases.

You should have a Master’s or PhD in CS, strong Python/PyTorch skills, and published research. Experience with transformers or foundation models is preferred and a passion for efficient,