As a Staff Software Engineer for Search Quality at Databricks, you will lead the technical direction of ranking, relevance, evaluation, and quality initiatives for the next-generation Search product. Your role will involve designing and building systems and models that ensure high-quality search results across diverse datasets. You will collaborate with research, product, and infrastructure teams to enhance retrieval quality for enterprise AI applications. Additionally, you will mentor senior engineers and shape the long-term vision for search relevance and quality.

• 10+ years of experience building large-scale search, ranking, recommendation, or ML-driven relevance systems.
• Deep expertise in Search Quality, including ranking models, signals, query understanding, and evaluation methodologies.
• Strong understanding of relevance metrics and evaluation frameworks.
• Familiarity with vector search, keyword search, hybrid retrieval, and embedding-based semantic retrieval.
• Solid foundation in algorithms, data structures, and system design for performance-critical ranking and retrieval systems.
• Proven ability to deliver high-impact technical initiatives with clear business or product outcomes.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
• Passion for mentoring, growing engineers, and fostering technical excellence.

• Lead the technical vision for Search Quality, shaping the ranking architecture and relevance modeling stack.
• Identify and solve challenges in ranking, query understanding, and hybrid retrieval.
• Design and train production-ready ranking and reranking models with strong guarantees around quality and efficiency.
• Partner closely with research, product, and infra teams to define metrics and evaluation methodologies.
• Drive end-to-end engineering efforts from early prototyping to production rollout.
• Build and operate resilient, low-latency services for ranking and evaluation.
• Champion excellence in ML and search engineering, mentoring teammates and elevating design and code quality.
• Shape Databricks’ long-term roadmap for retrieval quality and ranking infrastructure.