Joblaze summary

In this role, the Staff Software Engineer will focus on enhancing the search quality of Databricks' AI/ML-powered products by developing and deploying machine learning models for search relevance. Key skills include expertise in natural language processing, query understanding, and experience with large language models, alongside a strong foundation in computer science. This position is ideal for seasoned professionals with over a decade of experience in search relevance systems, particularly those who thrive in collaborative, technology-driven environments. Databricks emphasizes innovation in AI solutions, making this a pivotal role in shaping the future of their search capabilities.

Joblaze insights

Listed about a month ago — first seen on Joblaze September 6, 2026. Last confirmed on Databricks's careers page October 27, 2026.
AI/ML appears in 34.2% of 284 comparable staff ai/ml roles in United States; Natural Language Processing appears in 1.4% of 284 comparable staff ai/ml roles in United States.

Quick facts

How much experience is required?: At least 10 years of relevant experience for this Staff Software Engineer - Search Platform role.
What's the tech stack?: Joblaze extracted these technologies from the posting: AI/ML, Machine Learning, Natural Language Processing.
What seniority level is this role?: Databricks targets staff-level candidates for this position.
Is this full-time or contract?: Full-time for this Staff Software Engineer - Search Platform role at Databricks.

From the original posting

P-375

The Search team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks.

As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. We are focusing on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services.
Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration.
Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience.
Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
10+ years experience developing search relevance systems at scale in production or in high-impact research environments.
Experience applying LLM to search relevance
Experience in one or more of the following:

Query understanding
NLP
Text mining
Recommendations
Personalization
Discovery
Conversational AI

Strong understanding of computer science fundamentals.
Contributions to well-used open-source projects.

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

About Databricks

Benefits

Standard company text repeated across Databricks's postings is omitted here.

Staff Software Engineer - Search Platform

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