Amazon Data Services, Inc.
Technology
AppliedScientistII,PerimeterProtectionAppliedScience
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied Scientist II, Perimeter Protection Applied Science at Amazon Data Services, Inc.. Skills: AI, ML, Cybersecurity, Large language models. Design ML models. Develop ML models”
What You'll Achieve.
Protect AWS customers; Deliver production-grade systems; Provide robust protection; Provide adaptive protection; Provide forward-looking protection
Industry & Context.
Analyze large-scale datasets; Identify emerging threat vectors; Translate findings into solutions; Design and run experiments; Validate model performance; Iterate on approaches
What They're Looking For.
Must Have
2+ years building models, Master's degree and 2+ years experience, Experience in patents or publications, Experience programming in Java, C++, Python, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing, Experience with MxNet, Experience with TensorFlow
Nice to Have
PhD in computer science, computer engineering, or related field, Experience in designing experiments, Experience in statistical analysis of results, Knowledge of architectural concepts, Knowledge of algorithms, Knowledge of schedule tradeoffs, Knowledge of new opportunities, Experience in state-of-the-art deep learning models architecture design, Experience in deep learning training and optimization, Experience in model pruning, Experience applying theoretical models, Publications at top-tier peer-reviewed conferences or journals
What You'll Do.
Mitigate cyber threats
Mitigate DDoS attacks
Mitigate bot activity
Mitigate web application exploits
Analyze automated threats
Implement intelligent mitigation
Implement adaptive defense systems
Implement end-to-end ML solutions
Identify threat vectors
Maintain data pipelines
Support experimentation
Ensure production performance
Design security systems
Validate model performance
Iterate on approaches
Stay current with AI/ML advances
Apply relevant techniques
Improve detection capabilities
Improve protection capabilities
Contribute to design reviews
Participate in roadmap
Identify opportunities
How You'll Work.
Team & Collaboration
Collaborate with scientists; Collaborate with engineers; Design reviews; Knowledge sharing
Full Job Description
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 cybersecurit
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