Amazon Sr Applied Scientist Amazon Security Defensive 

United States, Washington, Seattle 

352055603

In this role you will be a founding member of a new science initiative on a ground breaking new product. You will develop key technological A.I. advancements and ML models that will power a new suite of tools. These tools will empower 200+ security engineers world wide to keep Amazon secure.As part of the Defensive Security organization you will enable Amazon to maintain customer trust through broad security initiatives. As the leading contributor of Defensive Security's A.I. initiatives, you will be on the forefront of resolving security findings at Amazon scale.Key job responsibilities
- You will derive novel M.L. models for classification, and prediction using LLMs/LMMs/LAMs.
- You will design and develop scalable ML models.
- You will work with large datasets (Petabyte scale).
- You will leverage large GPU clusters to train and deploy models.
- You will work closely within software/security engineering teams to deploy your models, and test the quality of their impacts.
- You will publish your work at major conferences/journals.
- You will create written communication briefing findings, and observations for executive leadership.
- You will mentor team members in the use of your AI models.A 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 and collaborate 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.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.