Senior Applied Scientist, Aws Security

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Senior Applied Scientist role focused on building and deploying AI/ML systems for cybersecurity threat detection and mitigation within AWS. The role involves analyzing threat data at scale, developing prototypes, and leading technical innovation to protect AWS customers.

What you'd actually do

  1. Design, build, and deploy AI/ML systems that process threat data at scale, running over petabyte-scale security logs with real-time inference
  2. Conduct thorough data analyses and develop prototypes for detecting otherwise-unknown security problems
  3. Independently frame ambiguous problems, and then define and deliver a research agenda with limited guidance
  4. Seek out, develop, and advocate for new technologies to solve scientifically-complex security problems
  5. Build consensus on scientific approaches, balancing analytic rigor with the operational urgency inherent to security

Skills

Required

  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience leading engineering teams as a mentor or tech lead
  • 3+ years of non-internship experience building machine learning models for business applications
  • Experience deploying AI/ML models into production systems with direct, verified customer impact
  • Non-internship experience of programming and/or scripting to solve real-world problems (e.g., in Python)

Nice to have

  • Experience with large scale distributed systems such as Hadoop, Spark etc.
  • Experience using AI/ML to solve problems in cybersecurity, fraud, or related areas
  • Experience building and deploying new GenAI

What the JD emphasized

  • building innovative AI/ML services
  • detect and automate the mitigation of cybersecurity threats
  • develop innovative security solutions at a massive scale
  • deploying AI/ML models into production systems with direct, verified customer impact
  • building and deploying new GenAI

Other signals

  • building innovative AI/ML services that protect cloud infrastructure
  • detect and automate mitigation of cybersecurity threats
  • develop innovative security solutions at a massive scale
  • deploying AI/ML models into production systems with direct, verified customer impact