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Shweta Chavan
Junior Computer Vision & ML Engineer specializing in autonomous perception systems
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About
LLM/RAG engineer who built a production-style multi-agent orchestrator for resume-to-recommendation workflows (PDF ingestion through screening and recommendations), emphasizing prompt tuning and strict JSON output contracts. Currently building a RAG application for an NGO using Airflow (DAGs + embeddings) and tackling messy, missing/imbalanced data; has hands-on retrieval stack experience (FAISS/HNSW, bge embeddings) and uses rigorous evaluation metrics for groundedness and hallucination control.
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Key Strengths
- Built and deployed a multi-module LLM orchestrator pipeline (resume PDF ingestion through recommendation)
- Strong workflow modularization and stage separation (Airflow DAGs; clean module boundaries)
- Reliability-focused engineering: logging, schema/format enforcement (JSON), unit + integration + adversarial testing
- LLM prompt optimization and output-structure control for production workflows
- RAG evaluation mindset using measurable metrics (retrieval precision, groundedness, hallucinations, latency/throughput, similarity)
- Retrieval system design for nuanced medical documents using FAISS + HNSW + bge embeddings for sub-linear ANN retrieval
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3 publications
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