About the job
At Databricks, we are dedicated to empowering data teams to tackle some of the world's most challenging issues , from realizing the next mode of transportation to fast-tracking medical advancements. Our mission involves constructing and managing the premier data and AI infrastructure platform, allowing our clients to leverage profound data insights to enhance their operations.
Search technology is integral to this endeavor. Through a combination of keyword retrieval, semantic similarity via vector embeddings, and hybrid methods, our Search technologies enable users to find, discover, and comprehend information within vast, intricate datasets. This technology fuels a wide array of applications, from Retrieval Augmented Generation (RAG) and AI assistants to recommendation engines, enterprise knowledge management, in-product search, and data exploration.
As a Staff Software Engineer specializing in Search Quality, you will steer the technical strategy for ranking, relevance, evaluation, and quality initiatives within Databricks' advanced Search product. You will architect and develop systems, models, and evaluation frameworks that guarantee our Search stack yields precise, high-quality outcomes across a variety of multimodal datasets and query patterns. Collaborating with research, product, and infrastructure teams, you will push the boundaries of retrieval quality for enterprise AI applications by integrating traditional information retrieval techniques with representation learning and neural ranking.
In addition to your technical contributions, you will help shape our long-term vision for relevance and quality, mentor senior engineers, and lead strategic initiatives that enhance the accuracy, dependability, and overall impact of Search across Databricks.
