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Kella Dhanush Venkata Sai
Junior ML Engineer specializing in Generative AI and LLM applications
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Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.
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Key Strengths
- Built and deployed an internal RAG-based knowledge assistant over PDFs/spreadsheets/support docs
- Improved retrieval quality using hybrid retrieval and metadata-enriched chunks
- Reduced hallucinations via strict context-only prompting with required source citations and confidence checks
- Optimized production performance with model quantization and containerized deployment
- Designs AI workflows in testable stages with unit tests, real use-case scenarios, and post-deploy monitoring
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