Staff ML Software Engineer, Ads Modeling, Personalization, and Quality

Google•Mountain View, CA

11h•$207,000 - $300,000

About The Position

Google's software engineers build next-generation technologies that help billions of users connect, explore, and interact with information. This role works on projects critical to Google's needs and calls for versatility, leadership, and enthusiasm for solving new problems across the full stack. The role is part of App Ads, a rapidly growing Google Ads business. The team develops engineering innovations to improve App Ads quality and support business growth, building machine-learning models to predict users' interactions with ads and applying optimization techniques to help publishers monetize content and advertisers acquire engaged users. Google Ads applies machine learning and generative AI to its global advertising business. This work affects users by helping protect them from harm, improving ad quality, and optimizing advertiser campaigns. The team collaborates with partners including Google Research and DeepMind. The position focuses on designing deep-learning models that predict interactions with ad formats across Google's ad delivery channels, engineering input features, improving model efficiency and reliability, and resolving advertiser performance problems. It also involves working with Product Management, UX, and partner teams to deliver ad experiences and using data and metrics to evaluate products and inform business decisions.

Requirements

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 machine-learning design and infrastructure, such as model deployment, model evaluation, data processing, debugging, and fine-tuning.
5 years of experience testing and launching software products.
3 years of experience with software design and architecture.
5 years of experience with machine-learning or AI algorithms and tools, deep learning, or other AI/ML modeling.
Experience in the digital advertising ecosystem.

Nice To Haves

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 statistical modeling and experimentation or analysis.
Experience in quality or modeling engineering teams.

Responsibilities

Design deep-learning-based machine-learning models to predict users' interactions with different ad formats across Google's ad delivery channels.
Incorporate and engineer input features from ad creatives, publisher pages and content, and users' personalized ad history to improve model accuracy.
Improve the efficiency and reliability of machine-learning models by designing new 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.
Use data and metrics to evaluate product success and drive business decisions.