About this role
Summary: The Senior Software Engineer will build core infrastructure and developer tooling for Google Ads Safety, ensuring ML/LLM classifiers are safe, measurable, and reliable at scale. The role involves writing and testing code, leading design reviews, and collaborating with cross-functional teams to protect users and ad...
info_outline XIn most instances, this position requires in-person interviews as part of the hiring process. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience programming in C++. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture. Preferred qualifications: Master's degree or PhD in Computer Science or a related technical field. 5 years of experience with data structures and algorithms. 1 year of experience in a technical leadership role. Experience developing accessible technologies.
About the job 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. The Ads Safety team has a mission to ensure that Google Ads products and networks are safe, free from malware, fraud, and illicit products, compliant with global regulations, and that our users and advertisers have great experiences. Within Ads Safety, this team builds the core infrastructure, developer tooling, and automated safety guardrails that power every stage of an ML/LLM classifier's lifecycle. Our mission is to provide a seamless, standardized developer experience for authoring, evaluating, launching, monitoring, and decommissioning classifiers—ensuring that every launch across Ads Safety is safe, measurable, and reliable at Google scale. 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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google.
Responsibilities Write and test product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.