Work Experience

• Redesigned a search system combining advanced RAG techniques like query expansion, neural reranking, and conversation-aware memory and hybrid search for more accurate answers.

• Improved prompt design with chain of thought reasoning and expert knowledge.

• Cut application latency by 78% using optimization and caching.

• Reduced memory usage by 71% through optimized data handling.

• Streamlined the codebase by 45% with a cleaner, modular design.

• Built a LLM as a Judge evaluation pipeline to reduce manual effort.

• Developed REST APIs to scrape legal cases from various Indian courts, enhancing accessibility to legal information.

• Designed a Multi-Agent system using LangGraph to identify one-sided and red-flag clauses in legal contracts.

• Implemented advanced RAG techniques like hybrid search and metadata filtering for a legal QA chatbot.

• Scraped and formatted laws from the USA, Dubai, and Singapore to curate a dataset for LLM fine-tuning.

• Built a taxonomical dataset for five domains tailored to company-specific needs.

• Designed a time series pipeline using XGBoost with $sim$10,000 rows achieving 98.8% accuracy.

• Evaluated open-source text-to-speech models to enhance chatbot capabilities.