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Staff Software Engineer (Search Ranking)

Databricks

EngineeringBengaluru, IndiaApply directly

About the role

P-1408

The Applied AI team at [hidden] sits at the forefront of advancing AI/ML-powered products. [hidden]’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for [hidden]’ 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. In 2026, we will focus 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 [hidden]' 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 [hidden], 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 [hidden], 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 [hidden]

[hidden] 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 [hidden] Data Intelligence Platform to unify and democratize data, analytics and AI. [hidden] 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 [hidden] on Twitter, LinkedIn and Facebook.

Benefits

At [hidden], 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 [hidden], 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 [hidden] 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.

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