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The Mission
We are democratizing Data and AI for every enterprise user. Our vision is a world where anyone can master their organization’s data through Apps and AI Agents. We are building the retrieval backbone for two worlds: the high-precision context layer for AI agents and the intuitive search experience for people goal is the same: instant, accurate, and actionable insight.
The Role:
- As a Search Quality Engineer, you sit at the heart of this transformation. You aren't just building a search engine; you are building the contextual backbone of the entire company.
- You will own the quality of results for two distinct but deeply connected "users":
- The AI Agent: Optimizing the retrieval layer that allows LLMs to reason over data they weren’t trained on, ensuring they have the "ground truth" needed to synthesize accurate, high-stakes business actions.
- The Human User: Improving the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces.
The Technical Challenge
This isn't a solved problem. You will be tackling "Search" in its most evolved form:
- Hybrid Retrieval: Balancing traditional keyword-based search (for exactness) with semantic vector search (for intent).
- Dual-Optimization: Fine-tuning ranking models that satisfy both human readability and LLM-ready context.
- High-Stakes Accuracy: In a world of Agents, poor search quality leads to hallucinations. You will build the guardrails and relevance scoring that ensure our AI stays grounded in reality.
- Data Heterogeneity: Connecting the dots across structured SQL tables, unstructured docs, and real-time business metrics.
Why This is the Place to Be
- You will have a front-row seat to the Agentic revolution. If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let’s talk.
What We’re Looking For
- The IR Specialist: You know your way around Lucene/Elasticsearch, embeddings, and ranking algorithms.
- The Quality and Metrics Obsessive: You understand that "relevance" is subjective and love building evaluation frameworks (human-in-the-loop and LLM-based) to measure it. You are obsessed with relevance metrics (nDCG, MRR, Precision@K).
- The Bridge Builder: You’re excited to apply traditional Information Retrieval (IR) wisdom to the cutting-edge world of Retrieval-Augmented Generation (RAG).
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.
Skills Required
- Expertise with Lucene/Elasticsearch
- Experience with embeddings and semantic/vector search
- Experience building ranking models and IR algorithms for dual human/LLM optimization
- Experience designing evaluation frameworks and relevance metrics (nDCG, MRR, Precision@K)
- Familiarity with Retrieval-Augmented Generation (RAG) and integration with LLMs
- Experience working across structured (SQL) and unstructured data sources
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
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