Senior Staff Tech Lead Manager, Generative AI, Search Personalization

Provide technical leadership on high-impact projects.Facilitate alignment and clarity across teams on goals, outcomes, and timelines.Design, develop, test, deploy, maintain, and enhance large-scale software solutions.Refine and improve the personalization quality goals based on real user interactions and adoption of new personalized search capabilities.Lead a small team that works on deep, domain specific problems and works effectively with partner teams to iterate on quality at scale with speed.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 optimizing industry ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).5 years of experience with design and architecture; and testing/launching software products.2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). Preferred qualifications:Master’s degree or PhD in Engineering, Computer Science, or a related technical field.8 years of experience with data structures and algorithms.5 years of experience in a technical leadership role leading project teams and setting technical direction.3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.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.The Personalization quality team is charting new quality issues focused on relevance, accuracy of user context and ultimately efficiency of applying that context in producing the best search results. Improving the overall Search experience through these new dimensions is essential for enabling billions of users to search for anything, anxiety free with an experience that is uniquely tailored to them.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 - $364000 (USD) + 25% bonus target + equity + benefitsLearn more about benefits at Google.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 optimizing industry ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).5 years of experience with design and architecture; and testing/launching software products.2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).