Software Engineer III, AI/ML, Account Structure Intelligence

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 Account Structure Intelligence (ASI) team’s mission is to simplify the advertiser experience by transforming complex account management into an automated, AI-ready framework, empowering advertisers to capture all high-value traffic with minimal manual input. On the ASI team, you will design and build the core LLM-powered extraction engine responsible for processing advertiser URLs. You will bridge advanced Generative AI and large-scale data infrastructure to parse unstructured web pages into structured, queryable inventory representations. In this role, you will take ownership of end-to-end extraction workflows—from model exploration, training, and fine-tuning to building high-throughput batch and near-line production pipelines. You will collaborate with partner teams and fellow engineers to turn raw web content into high-fidelity signals that power customized ad creatives and landing page experiences across the entire Ads ecosystem. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . Apply LLMs to information retrieval, entity extraction, and structured schema generation from semi-structured and unstructured web content. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (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. Experiment with and implement prompt engineering, supervised fine-tuning, distillation, and model compression techniques to optimize accuracy, throughput, and inference cost. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience programming in Python or C++. 1 year of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), natural language processing, ML infrastructure, or specialization in another ML field. 1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging). Preferred qualifications: Master's degree or PhD in Computer Science or related technical fields. 2 years of experience with data structures or algorithms. Experience developing accessible technologies. Experience with Ads. Bachelor’s degree or equivalent practical experience. 2 years of experience programming in Python or C++. 1 year of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), natural language processing, ML infrastructure, or specialization in another ML field. 1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).