Join Google Cloud's innovative team as a Senior Staff Software Engineer, focusing on Workspace Search Quality. You will be at the forefront of developing next-generation search experiences that empower billions of users. This role offers the chance to work on critical projects, switch teams as needed, and drive innovation in a fast-paced environment. We seek versatile engineers with leadership potential, eager to tackle complex full-stack challenges and shape the future of productivity tools.

Our mission is to create intuitive and effective search experiences across Google Workspace products like Gmail, Chat, and Drive. You will leverage advanced Machine Learning (ML) technologies, implement significant user-facing changes, and revamp our evaluation frameworks. The impact of AI on the future of work is immense, and our products are leading the charge with features like AI-powered summaries and avatars. As part of this team, you will help define how productivity tools function in the coming years, collaborating with top talent and influencing the experience of a global user base.

Lead the end-to-end architecture, design, and implementation of search solutions, from natural language query understanding to deploying ML models for enhanced search quality.

Drive innovation by exploring and integrating cutting-edge ML techniques, algorithms, and architectures to significantly improve search relevance and user experience.

Own the technical vision and roadmap for key areas within Workspace Search, fostering collaboration with cross-functional teams to define and achieve strategic goals.

Establish and continuously refine evaluation frameworks and key performance indicators to accurately measure and track progress in search quality.

A Bachelor's degree or equivalent practical experience is required.

Minimum of 8 years of professional software engineering experience, with a strong focus on Information Retrieval (IR), Natural Language Processing (NLP), or Machine Learning (ML).

Demonstrated experience in launching large-scale, production-quality, user-facing systems.

Proven ability to design, implement, and optimize high-performance, distributed search or quality systems within production environments.

Preferred qualifications include expertise in embedding-based retrieval, vector search, query understanding, or the application of Large Language Models (LLMs) to search and recommendation systems. Experience managing system latency improvements and scalability enhancements is also highly valued, as is a background in defining metrics, analyzing user feedback, and conducting complex search experiments. Familiarity with agentic architectures, tool-calling, and RAG grounding layers, coupled with exceptional collaboration and communication skills, will be critical for aligning diverse stakeholders and navigating priorities.