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 any of the following areas: 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 Tensor Flow
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.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
Additional Information
Join the AWS Perimeter Protection team as an Applied Scientist, where 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 job 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 through 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.
Amazon Data · Seattle, WA