Applied Scientist II, Perimeter Protection Applied Science

Join the AWS Perimeter Protection team as an Applied Scientist. You will design and build AI/ML models that protect AWS customers from cyber threats at massive scale. You will work on challenging problems in threat detection, bot management, DDoS protection, and web application security—developing and deploying machine learning solutions that leverage techniques including large language models, generative AI, and agentic AI systems. Operating across all AWS regions and processing trillions of requests per week, you will collaborate with experienced scientists and engineers to deliver production‑grade, intelligent security systems that provide robust, adaptive, and forward‑looking protection for AWS customers worldwide. Key Responsibilities Design, develop, and evaluate ML models and algorithms for threat detection, anomaly detection, and mitigation of evolving cyber threats including DDoS attacks, bot activity, and web application exploits. Explore and apply large language models, generative AI, and agentic AI approaches to security challenges such as automated threat analysis, intelligent mitigation, and adaptive defense systems. Implement end‑to‑end ML solutions—from data exploration and feature engineering to model training, evaluation, and deployment into production systems. Analyze large‑scale datasets to uncover patterns, identify emerging threat vectors, and translate findings into effective ML‑based security solutions. Build and maintain data pipelines and model training workflows that support rapid experimentation and reliable production performance. Collaborate with software engineers to integrate ML models into low‑latency, high‑throughput security systems at cloud scale. Design and run experiments to validate model performance, measure impact, and iterate on approaches using rigorous scientific methodology. Stay current with recent advances in AI/ML—including LLMs, generative AI, and agentic systems—and cybersecurity research, applying relevant techniques to improve detection and protection capabilities. Contribute to design reviews and knowledge sharing. Participate in the team's scientific roadmap by proposing ideas and identifying opportunities to improve existing systems. Basic Qualifications 2+ years of building models for business application experience PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience Experience in patents or publications at top‑tier peer‑reviewed conferences or journals Experience programming in Java, C++, Python or related language Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing Experience with popular deep learning frameworks such as MxNet and TensorFlow Preferred Qualifications PhD in computer science, computer engineering, or related field Experience in designing experiments and statistical analysis of results Knowledge of architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members Experience in state‑of‑the‑art deep learning models architecture design and deep learning training and optimization and model pruning Experience applying theoretical models in an applied environment Have publications at top‑tier peer‑reviewed conferences or journals Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually #J-18808-Ljbffr Amazon Science