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Microsoft Senior Security Researcher 
Taiwan, Taoyuan City 
876333840

Yesterday

Required Qualifications

  • Master's Degree in Statistics, Mathematics, Computer Science or related field OR 5+ years experience in software development lifecycle, large-scale computing, modeling, cybersecurity, and/or anomaly detection.
  • 3+ years of experience with common threat analysis models (MITRE ATT&CK, Cyber Kill Chain, Diamond Model) and operationalizing detections at scale.
  • 3+ years of experience applying AI/ML techniques to security scenarios, including large language models and hosted AI platforms (Azure AI Foundry, Azure OpenAI Service).


Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

Microsoft Cloud Background Check:
This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.


Preferred Qualifications

  • Doctorate in Statistics, Mathematics, Computer Science or related field OR 6+ years experience in software development lifecycle, large-scale computing, modeling, cybersecurity, and/or anomaly detection
  • Experience with PySpark is highly desired but not necessary

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities
  • Apply advanced ML/AI techniques including anomaly detection on large scale security datasets to build high efficacy detections to protect the Azure 1P infrastructure. -
  • Lead hypothesis-driven threat research by designing AI-assisted detection authoring playbooks that correlate low fidelity events and generate detection logic.
  • Design and execute experiments that transform managed security operations, define measurable success criteria, and scale proven approaches into production workflows.
  • Collaborate with cross-functional teams—including security researchers, applied scientists and Software Engineers to translate research into actionable detections, automation, and investigation tools that enhance security posture for Azure infrastructure.
  • Operationalize ML/AI models at scale by building robust data pipelines, implementing labeling strategies, and ensuring model monitoring for fairness, drift, and performance in live environments.
  • Communicate research impact effectively through clear documentation, prototypes, and presentations.
  • Stay ahead of the evolving threat landscape by tracking attacker tradecraft, validating new AI techniques, and converting insights into proactive detections and mitigations that reduce environment risk.

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