YouTube aims to ensure the Creator Economy rewards high-value innovation over low-quality, automated content by measuring and mitigating risks associated with synthetic media. The role focuses on bridging detection and economics to encourage high-quality GenAI content while defunding abusive, low-effort generation.
Requirements
- Experience in Machine Learning.
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- Experience in reading and applying quantitative methodologies from the academic literature.
- Expertise working with Large Language Models, GenAI Evaluation, AI tools, or Multimodal Machine Learning.
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
- PhD in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
Responsibilities
- Develop the methodology for measuring low-quality synthetic content within the business generation ecosystem.
- Design methodologies to validate Large Language Model (LLM) performance on nuanced content tasks.
- Leverage LLMs to develop and deploy 'hybrid' and 'LLM-first' metrics that distinguish between creative and repetitive content.
- Apply sampling theory and optimization techniques to our north star metrics for business generation safety.
- Own the process of gathering, extracting, compiling, and analyzing data across sources via relevant tools (e.g., SQL, R, Python).
Other
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- PhD in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
