Detection Engineer (remote)

CrowdStrike CrowdStrike · Enterprise · United States · Remote

CrowdStrike is seeking a Detection Engineer to analyze adversary intrusions and create/modify security detections. The role also involves addressing customer requests regarding machine learning detection models. Experience with ML concepts is a plus.

What you'd actually do

  1. Review current product detections to ensure they are performing to the company standard
  2. Perform tasks to enable better-management of false positive detections
  3. Analyze binary files to determine their legitimacy
  4. Address internal questions and concerns regarding customer threat detections

Skills

Required

  • Exposure and understanding of different types and functionality of malware
  • Experience with reverse engineering malware, detection engineering, or threat hunting
  • Knowledge of programming and scripting languages, in particular Python
  • Fundamental understanding of attributes of binary files such as imports/exports and packers
  • Ability to demonstrate practical knowledge of research/collection skills and analytical methods
  • A creative approach to problem solving and closing detection gaps
  • An excellent understanding of at least one major operating system type, or a public cloud provider
  • Ability to break down complex problems into workable components

Nice to have

  • Experience in a security operations center, incident response, blue teaming, or similar
  • A thorough understanding of Windows OS internals and the Windows API
  • Familiarity with tools used in targeted and criminal cyber-intrusions
  • A background in exploit and vulnerability analysis, or read teaming
  • Knowledge of a variety of programming languages including C, C++, Java, and assembly
  • Intimate knowledge of public cloud infrastructure
  • Experience with machine learning, data science, or data science concepts
  • Familiarity with CrowdStrike product and services
  • BA/BS or MA/MS degree or equivalent experience in Computer Science, Information Security, or a related field

What the JD emphasized

  • machine learning detection models