Product Manager II, YouTube Recommendations
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in product management.
- 8 years of experience in a role preparing and delivering technical presentations to executive leadership.
- 8 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.
Preferred qualifications:
- 5 years of experience working on ranking or recommendation algorithms.
- 5 years of expereience reviewing and assessing ML/AI models.
- 5 years of experience operating with scaled human raters.
About the job
In this role, you will work on tools that sit at the intersection of machine learning models and the user experience, supporting recommendations system designed to anticipate viewer needs and connect them with content they want to watch, while helping creators find an engaged audience. As a part of this role, you will help elevate high-quality voices in areas where accuracy and quality are essential such news, personal finance, and medical or scientific information, using a variety of tools and collaborating with data scientists to build the next-generation evaluation framework used to measure the success of these initiatives.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we 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 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
- Define and drive the roadmap for the tools used to elevate high-quality voices across Home, Watch Next, and Shorts.
- Own the product strategy for all consumer-facing News features, including the Top News and Breaking News shelves, ensuring timeliness and reliability.
- Design and analyze A/B experiments to measure how our features impact both team goals and core user satisfaction metrics.
- Partner with Data Science to build a scalable, LLM-driven evaluation framework.
- Present your goal and impact regularly to executive leadership, navigating high-stakes trade-offs and driving alignment across Engineering, UX, and Policy.
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