About the job
As a pivotal leader of a dynamic team of search relevance engineers, your primary mission will be to assess and enhance the ranking and relevance of our AI-driven enterprise search applications. These applications harness the power of large language models (LLMs), necessitating your expertise in evaluating and optimizing RAG-based objectives such as summarization, groundedness of responses, and citation accuracy and completeness. You will steer the team through the comprehensive development of machine learning models, encompassing data synthesis, feature engineering, experiment design, evaluation, and more. Your team's work will be fundamental in refining our search relevance systematically as we expand to new clients, diverse data types, and unique use-cases, ultimately ensuring the ranking quality across all our enterprise search products.
Your team’s commitment to search quality is vital to the success of the company’s search product lines, with performance gauged by its enabling capabilities. You will empower your team members by facilitating rapid iterations on model enhancements, enabling them to refine ML metrics while understanding performance trade-offs and generalizability.
You will oversee the team’s technical direction, manage project timelines, and ensure the resilience, efficiency, and innovation of our machine learning-based search systems. Collaboration with search infrastructure and platform engineers, as well as partnerships with product, design, and customer success teams, will be essential in achieving our business objectives.
