Software Engineer, Workspace Search Quality
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software engineering with Information Retrieval (IR), Natural Language Processing (NLP) or Machine Learning (ML).
- Experience with launching user-facing, large-scale, production quality systems.
- Experience designing, implementing, and optimizing large-scale, high-performance, distributed search or quality systems in production environments.
Preferred qualifications:
- Experience with embedding-based retrieval, vector search, query understanding or Large Language Models (LLMs) applied to search/recommendation systems.
- Experience mamaging system latency improvements (e.g., progressive loading, perfecting techniques, or bypassing post-retrieval latency overhead) and scalability enhancements.
- Background in defining metrics, analyzing user-perception surveys, and running complex search experiments.
- Good understanding of agentic architectures, tool-calling, Retrieval-Augmented Generation (RAG) grounding layers.
- Exceptional collaboration and communication skills, with a proven ability todrive technical alignment with cross-functional stakeholders and navigate competing priorities.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.We are building Intuitive, and effective searching and finding experiences by enabling search journeys that bridge across Google Workspace products (e.g., Gmail, Chat, Drive, etc.). We have an ambitious roadmap for making Workspace Search excellent, including the usage of advanced Machine Learning (ML) technologies, significant user-facing changes, revamping our evaluation framework and more.AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.
Responsibilities
- Lead the architecture, design and implementation of end-to-end search solutions, from understanding natural language queries to developing and deploying machine learning models that significantly improve search quality.
- Drive innovation by exploring and integrating machine learning techniques, algorithms, and architectures to enhance search relevance and user experience.
- Own the technical goal and roadmap for critical areas of Workspace Search, collaborating with cross-functional teams to define and deliver on a strategic roadmap.
- Establish and refine evaluation frameworks and metrics to measure and track progress against key performance-indicators.
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