Enforcement Detection Analyst
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026. Google scores B on the Alion truth index.
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 directly 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. You may also be exposed to graphic, controversial, and sometimes offensive video content during team escalations in line with YouTube’s Community Guidelines.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Develop, implement, and lead strategies to enforce YouTube policies at scale, providing data-driven insights for effective abuse prevention using machine learning.
- Collaborate closely with stakeholders and partners in engineering, product and policy to drive complex anti-abuse solutions.
- Provide rapid incident response for abuse problems by operating independently, analyzing root causes, and implementing effective mitigation steps.
- Master complex technical concepts and systems to deliver impactful results, communicating technical findings clearly to various audiences.
- Design and refine prompts for Large Language Models (LLMs) to improve their accuracy in identifying and classifying abusive content through prompt engineering and data labeling.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- 5 years of experience with one or more of the following languages: SQL, R, Python, or C++.
- 5 years of experience managing and leading projects, defining project scope, goals, and deliverables, and working with multiple stakeholders.
- Experience using Large Language Models (LLMs) to automate the detection and mitigation of platform abuse, including spam, phishing, or violative content.
Preferred qualifications:
- Master's degree in Engineering, Computer Science, Mathematics, Statistics, a related technical field, or equivalent practical experience.
- 5 years of experience or familiarity with machine learning systems.
- 5 years of experience or familiarity with Trust and Safety scaled abuse detection.
- Demonstrated track record of leveraging LLMs and generative AI technologies to solve business problems.
- Developed problem-solving and analytical abilities with a proven history of going above and beyond to make operational improvements and solve complex problems.