Lead the future of Workspace Search quality at Google, impacting over a billion users across products like Gmail, Drive, and Calendar. This role is pivotal in driving a strategic shift towards AI-powered search, moving beyond keyword matching to advanced semantic retrieval and natural language understanding. Shape the evolution of productivity and collaboration tools for the next 5-10 years, working alongside Google DeepMind and exceptional leaders to build the next generation of AI-driven features.

This is an opportunity to influence how billions of users interact with information and to contribute to the forefront of AI's impact on the future of work. You will play a key role in defining and implementing innovative search experiences that enhance productivity and foster collaboration across Google's suite of tools.

Drive a culture of continuous improvement through data-driven insights. Ensure the robustness and reliability of production environments by overseeing debugging, performance tuning, and technical debt management.

Collaborate with the Technical Lead to shape and execute the technical roadmap, providing strong leadership for search and recommendation systems. Guarantee the end-to-end quality and reliability of models, from data ingestion and indexing to final serving.

Spearhead the development of cutting-edge Information Retrieval and Machine Learning systems, focusing on areas like embedding-based search, advanced ranking algorithms, and natural language query understanding.

Establish and implement comprehensive evaluation frameworks and success metrics. Leverage offline/online evaluations and user feedback to consistently enhance search relevance and user satisfaction.

Cultivate a high-performing engineering environment by offering active coaching, performance feedback, and tailored career development plans for engineers.

A Bachelor's degree or equivalent practical experience is required, along with 8 years of experience in managing and developing software engineering teams. This includes significant experience in performance management and fostering career growth.

Additionally, 5 years of experience in a people management or team leadership capacity is essential. Candidates must possess experience in software engineering within Information Retrieval (IR), Natural Language Processing (NLP), or Machine Learning (ML).

Proven experience in designing, implementing, and optimizing large-scale, high-performance, distributed search or quality systems in production environments is a prerequisite. A Master's degree or PhD in a relevant technical field is preferred, alongside experience with embedding-based retrieval, vector search, query understanding, or large language models applied to search systems.