info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience designing machine learning evaluation frameworks. Experience building automated rating for large-scale infrastructure. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 5 years of experience in a technical leadership role leading project teams and setting technical direction. Experience with Large Language Models (LLMs), agentic architectures, and generative AI evaluation methodologies. Experience driving the technical design, implementation, and deployment of infrastructure projects from end to end. Experience using AI tools and development assistants to prototype and deliver features. 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. As a Senior Tech Lead on the Search Evaluation Infrastructure team, you will pioneer and institutionalize Evaluation-Driven Development (EDD) as the core technical foundation for generative AI features across Search Verticals and International (SVI). By shifting evaluation earlier in the development lifecycle, we replace subjective quality assessments with objective, metrics-based from day one of product definition. In this role, you will establish high-quality evaluation rubrics, cultivate scalable automated rating infrastructure, and deliver continuous tracking systems to empower engineering teams to build with speed and absolute confidence. You will lead evaluation infrastructure efforts to ensure reliability, capacity, and effectiveness, reducing quality iteration cycles from hours to minutes. In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $365000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Design, develop, test, deploy, maintain, and enhance large-scale evaluation software and automated rating infrastructure. Provide technical leadership on high-impact projects, managing project priorities, deadlines, and deliverables. Drive technical project strategy, lead large-scale machine learning (ML) infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas. Manage automated rating system reliability, capacity, and effectiveness to reduce quality iteration cycles from hours to minutes. Facilitate alignment across teams, collaborating with platform and intelligence engineering counterparts to represent evaluation infrastructure in technical forums.