Join our dynamic team to shape the future of workspace search across Google's suite of products, including Gmail, Drive, and Calendar. We are transforming search from simple keyword matching to advanced AI-driven semantic retrieval and natural language understanding. This is a unique opportunity to impact over a billion users globally and influence how productivity tools will evolve in the next 5-10 years.

You will collaborate with cutting-edge AI researchers and exceptional leaders, contributing to innovative solutions that enhance collaboration and growth for users worldwide. Become part of a team building the next generation of productivity experiences.

Champion a data-driven culture to continuously improve system performance and reliability. You will oversee debugging, performance tuning, and technical debt management for robust production environments.

Partner closely with the Technical Lead to define and execute the technical roadmap for search and recommendation systems. Ensure end-to-end quality from data ingestion and indexing through to serving.

Drive the development of advanced IR and ML systems, including embedding-based search, ranking algorithms, and query understanding. Implement rigorous evaluation frameworks and utilize user feedback to enhance search relevance and satisfaction.

Foster a high-performing engineering culture by providing active coaching, performance feedback, and personalized career development for your team.

A Bachelor's degree or equivalent practical experience is required, along with a minimum of 8 years managing and growing software engineering teams, including experience in performance management and career development. Additionally, 5 years in a people management or team leadership role is essential.

Demonstrated experience in software engineering, specifically within Information Retrieval (IR), Natural Language Processing (NLP), or Machine Learning (ML) is crucial. You should also possess experience designing, implementing, and optimizing large-scale, high-performance, distributed search or quality systems in production.

Preferred qualifications include a Master's degree or PhD in a relevant technical field, and experience with cutting-edge technologies such as embedding-based retrieval, vector search, advanced query understanding, and large language models in search applications. Exceptional collaboration and communication skills are vital for aligning stakeholders and navigating competing priorities.