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
Low-latency, LLM-powered classification systems evaluating content safety and brand suitability at internet scale
Domain
Advertising technology, Generative AI, Adversarial Machine Learning
Deliverable
production ML models
Required skills
LLM-powered classification, multimodal content evaluation, adversarial ML, semantic understanding, real-time system design, measurement frameworks, research-to-production translation
Preferred skills
Unix/Linux, professional software development
Technologies
Java, C++, Python, LLMs, multimodal pipelines
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; Define measurement frameworks and drive continuous improvement; Translate research into production; Collaborate with software engineering teams to integrate experiments into large-scale production systems
Seniority
Senior, hands-on IC with research leadership
