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Job Details
Posted date: Jan 08, 2026
Location: Kirkland, WA
Level: Executive
Description
Lead technical strategy and roadmap for ML/AI initiatives in YouTube Ads, ensuring scalability, reliability, and performance with an emphasis on ad relevance and user experience.Design and develop scalable ML systems and infrastructure for billions of daily requests, prioritizing low-latency relevance predictions, driving selection of ML techniques and tools, and focusing on models that optimize for advertiser return on investment and positive user sentiment.
Mentor engineers, fostering excellence in building user-centric ad experiences and collaborating with product managers and researchers to define requirements and deliver high-impact features that improve ad relevance and user satisfaction.
Identify and mitigate technical risks, and balance short-term needs with long-term goals for sustainable ad relevance.
Stay current with ML/AI and advertising tech, identifying opportunities to enhance ad performance and user perception.
The YouTube Ads Machine Learning/Artificial Intelligence (ML/AI) team is a collaborative group of engineers and researchers pushing advertising technology boundaries. We develop and deploy advanced ML models and systems for the YouTube Ads ecosystem, covering: ad ranking and optimization, building models for relevant and engaging ads, optimizing for clicks, conversions and view-through rates by understanding user intent and context; targeting and audience segmentation, developing intelligent systems for precise ad targeting and effective audience segmentation, improving user experience through relevance; and new ad product innovation, exploring and implementing novel ML/AI techniques for new, impactful advertising solutions that are less disruptive and more integrated.
As a Principal Engineer for our YouTube Ads ML/AI team, you will be a technical leader, driving the architecture and implementation of critical ML systems for the future of YouTube advertising. Your focus will be on advancing ad relevance to enhance user experience, making ads a valuable part of their journey.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
Qualifications
Minimum qualifications: Master's degree in Computer Science, Machine Learning, or related quantitative field, with a focus on recommender systems, user modeling, or computational advertising, or equivalent practical experience. 15 years of experience in software development, including experience in ML/AI. Experience with distributed systems and cloud platforms (e.g., Google Cloud Platform). Experience in technical roles working with ML algorithms, statistical modeling, and data science principles applied to user-facing products.Preferred qualifications: PhD degree in Computer Science, a related technical field, or equivalent practical experience. Experience with large-scale data processing technologies for ad relevance models. Experience in designing, building, and deploying large-scale production ML systems for ranking, recommendations, or personalization. Experience in advertising technology, specifically ad serving, ranking, or optimization, with improvements in user ad experience, coupled with experience leading and delivering impactful ML/AI projects and demonstrating measurable improvements in ad relevance and user satisfaction. Proficiency in Python, C++, Java, or Go.
Extended Qualifications
Master's degree in Computer Science, Machine Learning, or related quantitative field, with a focus on recommender systems, user modeling, or computational advertising, or equivalent practical experience. 15 years of experience in software development, including experience in ML/AI. Experience with distributed systems and cloud platforms (e.g., Google Cloud Platform). Experience in technical roles working with ML algorithms, statistical modeling, and data science principles applied to user-facing products.Check out other jobs at Google.