Applied Scientist, Ads Brand Safety and Suitability
Core
Build AI-powered Brand Safety and Content Classification systems to protect advertisers from unsafe, unsuitable, or policy-violating content across web, mobile app, CTV, and audio advertising inventory.
Role type
Senior Applied Scientist (Adversarial ML & LLMs)
Builds
LLM-powered content classification systems, multimodal evaluation pipelines, and adaptive ML systems for real-time content safety.
Domain
Advertising technology, Generative AI, Adversarial Machine Learning
Deliverable
production ML models
Required skills
LLMs for semantic understanding, adversarial ML, multimodal content evaluation, real-time low-latency system design, algorithm design, distributed computing, Java/C++/Python
Preferred skills
Unix/Linux, professional software development
Technologies
LLMs, Java, C++, Python
Responsibilities
Own science strategy for AI-powered brand safety classification; Build LLM-powered content classification systems making billions of decisions/day; Develop multimodal evaluation pipelines reasoning across text, images, audio, and video; Design adaptive ML systems resilient to adversarial evolution; Translate research into production; Publish at peer-reviewed venues.
Seniority
Senior, hands-on IC