Senior Staff Software Engineer, Workspace Search Quality

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.

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.