Enforcement Detection Analyst, YouTube Trust and Safety

About the job

Fast-paced, dynamic, and proactive, YouTube’s Trust & Safety team is dedicated to making YouTube a safe place for users, viewers, and content creators around the world to create, and express themselves. Whether understanding and solving their online content concerns, navigating within global legal frameworks, or writing and enforcing worldwide policy, the Trust & Safety team is on the frontlines of enhancing the YouTube experience, building internet safety, and protecting free speech in our ever-evolving digital world.

As an Enforcement Detection Analyst on the YouTube Trust and Safety team, you will be responsible for ensuring that we effectively identify and remove disruptive content and users as quickly as possible, in an environment where hundreds of hours of new content is uploaded every minute, globally.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

Responsibilities

• Develop, implement strategies and solutions to enforce YouTube policies at scale. Deliver improvements to our performance metrics. Leverage programming skills to ensure solutions fit within complex Product and backend infrastructures.
• Work with the Policy and Operations teams to understand the ever-changing policy enforcement landscape, and with Engineering teams to develop and test new features that address operational needs.
• Provide rapid incident response for abuse problems, operating independently. Analyze and draw conclusions on root-causes and define and implement mitigation steps.
• Understand the abuse landscape, covering key vectors including insights towards drivers/intention of the abuse (why), methods to acquire accounts, gaps in our enforcement (how), etc.
• Design and refine prompts for LLMs to improve their accuracy in identifying and classifying abusive content and behavior, including prompt engineering, data labeling, and performance analysis.