Staff Software Engineer, Search Quality
Core
Drive technical direction of ranking, relevance, evaluation, and quality initiatives for Databricks' next-generation Search product, ensuring accurate results across diverse multimodal datasets.
Role type
Staff Software Engineer (Search Quality & Ranking)
Builds
Production-ready ranking and reranking models, evaluation frameworks, and low-latency services for retrieval quality.
Domain
AI/ML, Search, Information Retrieval, Enterprise Data Platforms
Deliverable
production ML models
Required skills
Large-scale search and ranking system design, relevance modeling, query understanding, hybrid retrieval, vector search, embedding-based semantic retrieval, algorithms and data structures, system design for performance-critical systems, ML model training and optimization, evaluation methodologies
Preferred skills
Strategic vision for relevance, mentoring senior engineers, cross-functional collaboration, product-oriented mindset
Technologies
Vector embeddings, neural ranking, hybrid retrieval, multimodal datasets
Responsibilities
Lead technical vision for 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; Partner with research, product, and infra teams to define metrics and experimentation strategies; Drive end-to-end engineering efforts from prototyping to production rollout; Build and operate resilient, low-latency services for ranking and relevance signal processing; Shape long-term roadmap for retrieval quality and retrieval-driven AI products.
Seniority
Staff, hands-on IC with strategic leadership
