Applied Security Scientist: Real-Time ML for Cloud Defense

Amazon; Arlington, Northern (VA, KY); Hybrid; USD 143,000 - 193,000; Full time

Job summary

Amazon is seeking an Applied Scientist to leverage analytics and machine learning to protect our cloud infrastructure from security threats. You will develop anomaly detection, predictive models, and real-time analysis systems across AWS infrastructure, using Python and ML techniques.

The team emphasizes collaboration, inclusivity, and flexible work arrangements. You will work with peers across Maryland and Virginia, delivering results during core hours while maintaining a strong security

Qualifications

• 3+ years building models for business applications.
• PhD or Master’s plus 4+ years in CS/CE/ML or related field.
• Experience with patents or publications at top-tier conferences/journals.
• Proficient in Java, C++, Python or related language.
• Strong background in algorithms, data structures, data mining, parallel and distributed computing.

Responsibilities

• Analyze large-scale security data using statistical methods and data mining techniques.
• Create automated systems for real-time pattern recognition and risk assessment.
• Build data pipelines and ETL processes to handle massive security datasets.
• Translate complex analytical findings into actionable security insights.
• Run experiments to assess potential risk of security responses.
• Expand existing LLM agent pipelines and improve security postures.
• Analyze post mortems to understand signals that could have prevented incidents.

Skills

Java

C++

Python

Machine Learning

Education

PhD in CS/CE/ML

Master's in CS/CE/ML

Tools

Unix/Linux

AWS SageMaker

Job description

Amazon is seeking an Applied Scientist to leverage analytics and machine learning to protect our cloud infrastructure from security threats. You will develop anomaly detection, predictive models, and real-time analysis systems across AWS infrastructure, using Python and ML techniques.

The team emphasizes collaboration, inclusivity, and flexible work arrangements. You will work with peers across Maryland and Virginia, delivering results during core hours while maintaining a strong security