Staff Software Engineer, YouTube Ads Marketplace Optimization

Google’s software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We’re looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will help lead a team of ML/AI/SW engineers to grow the YouTube Ads business by understanding user interest and recommend ads that are aligned with user interest (i.e., YT’s ad user models). The YouTube Ads User Models are a suite of large-scale AI systems designed to model users’ commercial interests by leveraging Google-wide data sources approved for advertising purposes. Designed for multi-task learning across various surfaces, these models are applied to numerous downstream tasks, including retrieval, user action prediction, and knowledge distillation for training more compact models.

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, * Design, develop, test, deploy, maintain, and enhance large scale software solutions.

• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Lead the design and implementation of recommendation systems, optimize ML infrastructure, and guide the development of model architecture.

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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor’s degree or equivalent practical experience.

• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows., * Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 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, matrixed organization involving cross-functional, or cross-business projects.