GenAI Security Scientist for Cloud Threat Detection

Amazon Web Services (AWS); Maryland; On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs

Job summary

Amazon Security is seeking an Applied Scientist to analyze data with GenAI and ML techniques to build and deploy services that detect and mitigate cybersecurity threats across AWS infrastructure. You will collaborate with software engineers, security engineers, and fellow scientists to create scalable security solutions using SageMaker, Bedrock, and EMR.

The role emphasizes delivering high-quality results in a fast-paced environment with a strong coding bar for production-grade ML systems.

Qualifications

• PhD or Master’s in CS/CE/ML or related field with 4+ years of relevant experience
• Patents or publications in top-tier venues are a plus
• Proficient in Java, C++, Python or similar languages
• Strong knowledge of algorithms, data structures, and high-performance computing

Responsibilities

• Design, build, and deploy AI/ML systems processing threat data at scale
• Enhance and expand LLM agent pipelines for threat detection and response
• Analyze data and prototype approaches to detect unknown security issues
• Analyze post-mortems to identify data signals that could have prevented incidents
• Build data pipelines and ETL processes for massive security datasets

Skills

Java

C++

Python

Algorithms

Data structures

Numerical optimization

Data mining

Education

PhD or Master’s in CS/CE/ML or related field

Tools

Unix/Linux

Software development practices

Job description

Amazon Security is seeking an Applied Scientist to analyze data with GenAI and ML techniques to build and deploy services that detect and mitigate cybersecurity threats across AWS infrastructure. You will collaborate with software engineers, security engineers, and fellow scientists to create scalable security solutions using SageMaker, Bedrock, and EMR.

The role emphasizes delivering high-quality results in a fast-paced environment with a strong coding bar for production-grade ML systems.