Related skills
rag large language models vector search information retrieval embeddings📋 Description
- Define and lead independent IR research for reusable agent components.
- Drive enterprise retrieval and search strategy, including vector search.
- Develop algorithmic innovations for retrieval within LLMs.
- Build benchmarks for retrieval, text embeddings, and LLM data quality.
🎯 Requirements
- 5+ years of experience.
- PhD in CS with strong NLP and IR foundations.
- Develop methods to extend model capabilities, reliability, and safety.
- First-author ML/systems papers (EMNLP/ICLR/ACL/NeurIPS) on optimization.
🎁 Benefits
- Comprehensive benefits and region-specific details via linked page.
- Eligible for annual bonus, equity, and listed benefits.
- Global offices; HQ in San Francisco.
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