Research Engineer, Foundation Model

The role

Research Engineers design experiments, contribute to papers, and write code to turn architectural ideas into trained models. You will work on scaling transformer architectures, building multimodal models, and designing architectures for time series and anomaly detection.

What you will do

• Design and test novel architectures
• Run ablations
• Analyze scaling behavior
• Write training and evaluation infrastructure
• Design experiments
• Contribute to papers
• Write code that turns architectural ideas into trained models

Required qualifications

• Master's or PhD in Computer Science or a related field
• 3+ years of experience building ML systems in research or industry
• Publications at top ML venues (NeurIPS, ICML, ICLR, etc.) or equivalent demonstrated research impact
• Deep proficiency in Python, PyTorch, and the broader ML and data science ecosystem (scikit-learn, pandas, NumPy)
• Strong software engineering practices
• Experience implementing and training neural network architectures, ideally transformers or foundation models
• Solid understanding of training dynamics, scaling behavior, and common failure modes in deep learning systems
• Genuine interest in model efficiency

Nice to have

• Experience at an early-stage startup or as a founding engineer
• Contributions to open-source ML libraries or tools
• Experience with model distillation, inference optimization, or on-device ML
• Background in tabular data, time series, or other structured data

About the company

Prior Labs is an independent frontier AI lab backed by SAP that pioneers tabular foundation models. The team is small and highly selective with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN.