Senior Applied Scientist - ML for Scalable App Security

Amazon Web Services (AWS); New York (NY); On-site; USD 184,000 - 249,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Data Services, Inc. in New York seeks an Applied Scientist III to invent and deliver ML-driven systems that transform how Amazon prioritizes and mitigates security risks at scale.

The role sits at the intersection of data science, ML, and security operations, leveraging large-scale datasets to build models that guide security resources and decision making. You will deploy production ML pipelines on AWS and collaborate with security engineers and TPMs.

Qualifications

• 3+ years building ML models for business use cases.
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• Experience with neural deep learning methods and ML.

Responsibilities

• Lead ML model design, development, and deployment for application security prioritization and risk assessment.
• Frame ambiguous security problems into well-defined scientific challenges.
• Architect production-grade ML pipelines on AWS services (S3, Glue, SageMaker).
• Develop graph-based models capturing relationships between apps, services, teams, and vulnerabilities.
• Drive the scientific agenda with experiments and rigorous evaluation.
• Collaborate with security engineers, data engineers, and TPMs to translate outputs into actionable intelligence.
• Establish scientific rigor with peer review and reproducible results.
• Publish results at peer-reviewed venues when appropriate.

Skills

Java

C++

Python

Deep learning

Education

PhD or MSc + 6+ years applied research

Tools

TensorFlow

Scikit-learn

Spark

MXNet

Neptune

Job description

Amazon Data Services, Inc. in New York seeks an Applied Scientist III to invent and deliver ML-driven systems that transform how Amazon prioritizes and mitigates security risks at scale.

The role sits at the intersection of data science, ML, and security operations, leveraging large-scale datasets to build models that guide security resources and decision making. You will deploy production ML pipelines on AWS and collaborate with security engineers and TPMs.