Senior Applied Scientist Real-Time ML Security

Amazon Web Services (AWS); Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Job summary

Amazon Data Services, Inc. is seeking a Senior Applied Scientist to design, build, and scale AI-driven security solutions for AWS. You will own the full ML lifecycle, from research to production deployment, accelerating real-time threat detection across services like WAF, DDoS protection, and Bot Management.

The role emphasizes scalable systems, low latency inference, and collaboration with software teams. You will contribute to production ML pipelines, feature engineering, and model evaluation

Qualifications

• 3+ years of building machine learning models for business applications.
• PhD or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related languages.
• Experience with neural deep learning methods and ML.
• Experience using managed ML/AI solutions.

Responsibilities

• Design, build, and deploy production-grade ML models and systems for real-time threat detection at cloud scale.
• Own the full ML lifecycle from problem formulation to production deployment and monitoring.
• Architect and optimize ML pipelines, training infrastructure, and serving systems with low latency.
• Bridge research and production by turning novel ML approaches into robust systems.
• Collaborate with software engineers to integrate ML models into distributed security services.
• Analyze production data to identify patterns and improve detection capabilities.
• Mentor junior scientists and engineers to raise science and engineering standards.

Skills

ML model development

Programming (Java C++ Python)

Deep learning

Applied ML in business

Managed ML/AI solutions

Education

PhD or MS + 6+ years experience

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Job description

Amazon Data Services, Inc. is seeking a Senior Applied Scientist to design, build, and scale AI-driven security solutions for AWS. You will own the full ML lifecycle, from research to production deployment, accelerating real-time threat detection across services like WAF, DDoS protection, and Bot Management.

The role emphasizes scalable systems, low latency inference, and collaboration with software teams. You will contribute to production ML pipelines, feature engineering, and model evaluation