Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Design new deep learning based ML models to predict users’ interaction with different ad formats across Google’s various ad delivery channels.
Incorporate and engineer input features from ad creatives, publisher pages/content, as well as users’ personalized ad history to improve models’ accuracy.
Improve the efficiency and reliability of ML models by designing novel model architectures and adopting development and release processes.
Debug and troubleshoot advertiser performance problems.
Work with Product Management, UX, and partner teams to design and deliver new ad experiences. Leverage data and metrics to help evaluate product success and drive business decisions.
Minimum qualifications
Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience with ML/AI algorithms and tools, deep learning or other AI/ML modeling.
Experience in the digital Ads ecosystem.
Preferred qualifications
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a complex organization involving cross-functional, or cross-business projects.
Experience with advertising products, quality work in ads, or with statistical modeling and experimentation/analysis.
Experience in quality or modeling engineering teams.
Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience with ML/AI algorithms and tools, deep learning or other AI/ML modeling.
Experience in the digital Ads ecosystem.
