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. #J-18808-Ljbffr Ataraxis AI