Senior Applied Scientist, AWS Security

Overview

Senior Applied Scientist role focusing on GenAI, machine learning, and cybersecurity to build innovative AI/ML services that detect and mitigate threats in AWS infrastructure. Collaborate with software engineers, security engineers, and other scientists to deploy scalable security solutions across AWS, protecting customers and preserving trust.

• Design, build, and deploy AI/ML systems that process threat data at scale, including petabyte-scale security logs with real-time inference
• Conduct thorough data analyses and develop prototypes to detect unknown security problems
• Independently frame ambiguous problems and define a research agenda with limited guidance
• Seek out, develop, and advocate for new technologies to solve scientifically complex security problems
• Build consensus on scientific approaches, balancing analytic rigor with operational urgency in security
• Mentor and develop teammates both technically and professionally
• Publish patents and peer-reviewed articles; present research internally and externally

This team is part of Amazon Active Defense, focused on bringing automation at scale to AWS Security. Teams include security engineers, data/applied scientists, and software developers working to launch big data analytics that can automatically detect and mitigate threats within AWS in near-real-time. The team focuses on detecting and stopping advanced actor activities in internal AWS resources.

Review relevant blogs for example past projects you could have led:

• https://(Use the "Apply for this Job" box below).-scale
• https://-threats

Amazon Security values diverse experiences. If you do not meet all qualifications, we encourage you to apply. If your career is just starting or follows a non-traditional path, consider applying.

Security is central to customer trust and experiences. We offer roles across cloud, devices, retail, entertainment, healthcare, operations, and physical stores, with opportunities to accelerate careers.

Ongoing DEI events and learning experiences foster curiosity and celebrate diverse ideas and perspectives.

Continuous learning, knowledge-sharing, and career-advancing resources help you grow as a professional.

Flexible work hours and arrangements support work-life harmony.

• PhD, or Master’s degree with 6+ years of applied research experience
• Experience leading engineering teams as a mentor or tech lead
• 3+ years of non-internship experience building ML models for business applications
• Experience deploying AI/ML models into production with verified customer impact
• Non-internship programming/scripting experience (e.g., Python)

• Experience with large-scale distributed systems (e.g., Hadoop, Spark)
• Experience applying AI/ML to cybersecurity, fraud, or related areas
• Experience building and deploying GenAI applications
• Experience with AWS or other cloud services (Sage Maker, Bedrock, EMR, Glue, Lambda, S3, etc.)

Amazon is an equal opportunity employer and does not discriminate on protected status. If you require a workplace accommodation during the application or hiring process, including for interviews or onboarding, please visit amazon.jobs for more information. If the country/region you’re applying in isn’t listed, contact your Recruiting Partner.

The base salary range for this position is listed below. Compensation includes sign-on payments and RSUs, determined by experience, qualifications, and location. We offer comprehensive benefits including health insurance, 401(k) matching, PTO, and parental leave. Learn more about our benefits s/en/benefits.

USA, WA, Seattle -  –  USD annually

Company:  Services LLC

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