Senior Staff Software Engineer, Search Ads Monetization

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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. GenAI is fundamentally transforming how people explore the web. As Search experience rapidly evolves with AI Overviews and AI Mode, the commercial engine that powers it must co-evolve. Our team sits at the exact intersection of user intent and monetization on search across both search results page (SRP) and we leverage machine learning and LLMs to reimagine the commercial journey across Google Search and Lens, ensuring we deliver value to users, advertisers, and Google’s long-term business. 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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google . Leverage AI/ML advancements, including LLMs and Agentic AI, to solve critical optimisation problems across search ads, from product innovation to agentic automation. Drive 10x better ads experiences compared to what we have today in the world of AI. Identify gaps in existing engineering processes and solve using AI-driven automation. Collaborate with teams across Search and Ads and cross-functional partners - Product Management, Data Science and UX. Build relationships with AdsAI, GDM and other Ads partners to jointly explore more in leveraging AI in ads. Design, build, and maintain self-service tools and platform features that embed these advanced AI/ML quality evaluation methods. Architect scalable systems for deploying and serving AI/ML models specifically for data quality assessment tasks. Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of software development experience in one or more programming languages, data structures, and algorithms. 8 years of experience with ML/AI algorithms, tools, deep learning, or other AI/ML modeling. 8 years of experience testing, maintaining, or launching software products, and 5 years with software design and architecture. 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, evaluation, data processing, debugging, fine-tuning). 2 years of experience with GenAI techniques (e.g., LLMs, multimodal, large vision models) or GenAI-related concepts (language modeling, computer vision). Preferred qualifications: PhD in Computer Science, Statistics, or related fields. Experience in GenAI related model fine tuning, large language models building or product enablement exploration. Significant experience in software development, with proficiency in languages like C++ and Python. Experience in successfully applying GenAI and machine learning approaches to real-world content problems. Experience building, experimenting and deploying AI-first systems and processes into production. Deep familiarity with Search/Ads infrastructure, auction mechanics, or generative AI models.