Amazon Senior Applied Scientist AI Security 

United States, California 

763861827

Key job responsibilities
• Research and develop accurate and scalable methods to solve our hardest AI security problems
• Lead and partner with applied scientists, software development engineers, and security engineers to drive modeling and technical design for a foundational GenAI-based security serviceA day in the life
A day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets, working with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created.Diverse Experiences — Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Training & Career Growth — We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.

- 5+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- PhD, or Master's degree and 6+ years of applied research experience
- Experience with making Large Language Models (LLMs) effective

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with prompt engineering, designing retrieval augmented generation frameworks for boosting a LLM's effectiveness
- Experience translating business needs into technical requirements
- Excellent communication skills with both technical and non-technical audiences
- Strong problem-solving ability and the ability to work in ambiguous and constantly evolving environment