ML Researcher, Autonomous Security

Job description

The Information Security Machine Learning (ISML) team empowers information security by harnessing patterns and insights from vast amounts of data to predict, detect, and respond; transforming reactive security into autonomous protection. We are seeking a highly innovative and experienced ML Researcher specializing in streaming threat detection over provenance graphs to join our dynamic team. As an ML Researcher on Autonomous Security, you will be instrumental in advancing the state-of-the-art in ML for cybersecurity, focusing on developing dynamic, adaptive, and robust security solutions that can operate with near or full autonomy in low-resource, on-device, and real-time streaming environments. Your work will bridge cutting-edge academic research with practical, real-world deployment challenges, contributing to the next generation of Apple’s security capabilities by significantly reducing detection lag and memory consumption compared to traditional methods. The ML Researcher will conduct pioneering research in streaming provenance-based intrusion detection systems (Prov-IDS), leveraging advanced machine learning, deep learning, and related AI fields. This role will focus on designing and implementing novel approaches for fine-grained, process-level threat detection over real-time event streams, specifically utilizing provenance graphs. You will be responsible for developing and evaluating iterative embedding techniques using sequential neural networks (e.g., RNNs, GRUs) that can process entire provenance…