Member of Technical Staff, Foundation Models

Responsibilities

• Design and implement novel self-supervised learning methods for training foundation models.
• Translate machine learning papers into production-ready code.
• Build robust model evaluation frameworks.
• Disseminate the results by co-authoring research papers and abstracts.
• Collaborate with a multidisciplinary team of engineers and scientists.
• Co-mentor junior members of the team.

Qualifications

• PhD degree in machine learning or statistics.
• Passion for research, attention to detail and ability to drive tasks to completion.
• Strong preference will be given to candidates with papers in A* conferences (e.g. ICML, ICLR, NeurIPS, CVPR).
• Excellent understanding of core machine learning concepts.
• Excellent knowledge of the foundations of statistics, linear algebra, probability and machine learning.
• Excellent skills in Python and PyTorch.
• Experience in deep learning and self-supervised learning.
• Experience in survival analysis, multi-modal learning, domain adaptation, causal inference, model interpretability and computational pathology is a bonus.

Pay

Compensation Range: $100K - $300K