Senior Researcher - Security - Microsoft Research

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Research Sciences

This role focuses on researching and developing next-generation intrusion detection systems by leveraging large-scale security event logs and applying advanced data processing and machine learning techniques. The goal is to achieve accurate and rapid detection of sophisticated attacks.

What you'd actually do

  1. Analyze large‑scale, heterogeneous security event logs spanning endpoints, identities, cloud services, and networks.
  2. Develop and train novel machine learning and statistical models for intrusion detection, anomaly detection, and adversarial behavior discovery.
  3. Design and prototype scalable data processing and analytics platforms capable of operating on high‑volume, high‑velocity security data, with a focus on low‑latency detection.
  4. Explore and apply advanced techniques such as graph‑based modeling, streaming computation, and representation learning to improve detection accuracy and timeliness.
  5. Collaborate closely with other researchers, product teams, and engineering partners to transition research ideas into practical systems with real‑world impact.

Skills

Required

  • Machine learning
  • Statistical modeling
  • Data mining
  • Systems
  • Large-scale data analysis
  • Streaming data processing
  • Distributed data processing

Nice to have

  • Graph-based modeling
  • Representation learning
  • Security expertise

What the JD emphasized

  • Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 4+ years related research experience OR equivalent experience.
  • A PhD (or equivalent experience) in computer science or a related field, with a strong research background in security, machine learning, data mining, systems, or a closely related area.

Other signals

  • Develop and train novel machine learning and statistical models for intrusion detection, anomaly detection, and adversarial behavior discovery.
  • Explore and apply advanced techniques such as graph-based modeling, streaming computation, and representation learning to improve detection accuracy and timeliness.
  • Collaborate closely with other researchers, product teams, and engineering partners to transition research ideas into practical systems with real-world impact.