Principal Applied Scientist, Trusted Supply, Amazon Ads
Core
Define and drive the science vision for Brand Safety, Suitability, and Risk Hunting to protect advertisers from unsafe content, fraud, and privacy threats across Amazon Advertising surfaces.
Role type
Principal Applied Scientist (Science Leadership)
Builds
Advanced algorithms and infrastructure systems for brand safety classification, content suitability scoring, risk hunting, and privacy-preserving measurement.
Domain
Computational advertising, trust & safety, fraud detection, privacy-preserving ML
Deliverable
production ML models
Required skills
NLP, Computer Vision, multi-modal learning, large-scale distributed ML systems, Python, systems languages (Java/C++/Scala), team leadership, scientific rigor, peer-reviewed publications
Preferred skills
GenAI/LLM-based classification, adversarial machine learning, anomaly detection, privacy-preserving techniques (federated learning, differential privacy), real-time low-latency inference
Technologies
Python, Java, C++, Scala, distributed ML frameworks
Responsibilities
Set multi-year research directions and publication roadmap; influence modeling frameworks across brand safety and traffic quality; act as a thought leader in industry forums; hire and mentor a team of applied scientists; partner with engineering to build scalable production systems; translate science capabilities into advertiser-facing products.
Seniority
Principal, strategy & mentorship
