Member of Technical Staff, Foundation Models

What you'll do

• Design and implement self-supervised learning methods for training foundation models.
• Translate machine learning papers into production-ready code and build model evaluation frameworks.
• Co-author research papers and abstracts, collaborate with engineers and scientists, and co-mentor junior team members.

What they ask for

• PhD degree in machine learning or statistics.
• Excellent understanding of core machine learning concepts and foundations of statistics, linear algebra, probability, and machine learning.
• Excellent skills in Python and PyTorch.
• Experience in deep learning and self-supervised learning.

Nice to have

• Papers in A* conferences such as ICML, ICLR, NeurIPS, or CVPR.
• Experience in survival analysis, multi-modal learning, domain adaptation, causal inference, model interpretability, or computational pathology.

Pay

$100K – $300K USD (base salary)

Tools

Python, PyTorch

AI focus

Research and development of self-supervised foundation models for clinical data, including methods for predicting patient outcomes and treatment response.