Amazon Senior Applied Scientist AWS Vulnerability Management Third Party Software 

United States, Texas, Arlington 

951190981

In this role, you'll be at the forefront of addressing one of the most critical challenges in cloud security today: managing the risks associated with third-party software. With the increasing frequency and sophistication third party vulnerabilities, your work will be crucial in safeguarding AWS environments against vulnerabilities that can arise from external components integrated into our infrastructure.You'll leverage your expertise in generative AI and machine learning to develop innovative approaches for identifying, assessing, and remediating security risks in third-party software. Your solutions will help bridge the gap between rapid innovation and robust security practices, ensuring that the software packages our builders use are not only efficient but also comply with AWS Vulnerability Management's (AVM) security standards.We're looking for someone who can think strategically about both mid-term tactical improvements and long-term security innovations. You'll be instrumental in establishing a data-driven decision framework that will guide our security measures, ensuring they're not only effective but also optimized for builder efficiency.Your role extends beyond just technical innovation. As a senior member of the team, you'll be a thought leader in the field of AI-driven security, contributing to the broader Amazon Science community and potentially publishing your findings in top-tier scientific venues. You'll also mentor team members, sharing your expertise and helping to cultivate the next generation of security innovators at AWS.
Key job responsibilities
1. Lead research and development of generative AI solutions to address security challenges in Vulnerability Management.
2. Develop and implement data-driven decision frameworks to analyze patterns in the package environment and quantify the impact of security improvements on builder productivity.4. Design and conduct experiments to solve complex security problems
5. Develop scalable, AI-driven solutions to efficiently respond to vulnerabilities in software packages.
6. Create and implement long-term strategic plans for integrating generative AI into AWS security practices.8. Mentor team members and provide expertise on a range of machine learning topics related to security.A day in the life

- 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.
- Experience with conducting research in a corporate setting
- Experience in model training and fine-tuning, in-context learning, and AI agents