RDQ326R95
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration.
As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks’ next-generation Search product. You’ll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns. You’ll work across research, product, and infra to push the frontier of retrieval quality for enterprise AI applications — blending traditional information retrieval techniques, representation learning, and neural ranking.
Beyond hands-on contributions, you will help define our long-term vision for relevance and quality, mentor senior engineers, and lead strategic efforts that raise the accuracy, reliability, and product impact of Search across Databricks.
The impact you will have:
- Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Databricks’ next-generation retrieval experiences.
- Identify and solve challenges in ranking, query understanding, and hybrid retrieval — advancing state-of-the-art techniques in vector, keyword, and multimodal search.
- Design and train production-ready ranking and reranking models with strong guarantees around quality, latency, and resource efficiency.
- Partner closely with research, product, and infra teams to define metrics, evaluation methodologies, and experimentation strategies for new retrieval features and model architectures.
- Drive end-to-end engineering efforts — from early prototyping to production rollout — ensuring correctness, reliability, and measurable improvements to relevance.
- Build and operate resilient, low-latency services for ranking, evaluation, and relevance signal processing.
- Champion excellence in ML and search engineering, mentoring teammates and elevating design, code quality, and scientific rigor across the team.
- Shape Databricks’ long‑term roadmap for retrieval quality, ranking infrastructure, and the foundations for retrieval-driven AI products.
What we look for:
- 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.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$165,300—$219,675 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
**Benefits
**At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.