Related skills
elasticsearch rag lucene embeddings mrr📋 Description
- Build the contextual backbone for company search quality.
- Own result quality for AI Agents and Human Users.
- Improve retrieval so LLMs reason over data with ground truth.
- Enhance traditional search for assets with high recall.
- Hybrid retrieval: keyword search plus semantic vector search.
- Data sources span SQL tables, unstructured docs, and real-time metrics.
🎯 Requirements
- Lucene/Elasticsearch experience
- Embeddings and ranking algorithms
- Evaluation frameworks: human-in-the-loop and LLM
- Relevance metrics: nDCG, MRR, Precision@K
- IR for Retrieval-Augmented Generation (RAG)
- Semantic search and hybrid retrieval concepts
🎁 Benefits
- Regional benefits details via the provided link
- Work with a global, diverse engineering team
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