Staff Software Engineer, Ads Content Safety

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. 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 . Define technical roadmaps and deliver models and agents to automate policy enforcement, improve velocity, and reduce user harm. Drive rapid prototyping and experimentation on architectural options for next-generation consumer trust enforcement using AI and LLM solutions. Identify and implement architecture improvements to build multi-tiered systems that manage massive query volumes and resolve complex policy cases. Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Provide technical leadership, mentor distributed engineering teams, and facilitate alignment on goals, outcomes, and timelines. Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products. 5 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent. 3 years of experience with software design and architecture. Experience integrating generative AI tools or LLM interfaces into workflows. Preferred qualifications: 5 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. Experience with Generative AI, LLMs, prompt engineering, and model distillation techniques, or the ability to rapidly master and guide team architectures in these spaces. Excellent communication skills working with cross-functional partners, privacy, and legal. Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products. 5 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent. 3 years of experience with software design and architecture. Experience integrating generative AI tools or LLM interfaces into workflows.