About Me
PROFESSIONAL SUMMARY AI/ML Research Engineer with 1.5+ years of hands-on experience building RAG pipelines, document understanding systems, and LLM-powered applications. Directly relevant to multimodal PDF-to-vector work: built production RAG systems achieving 90%+ retrieval precision over 500+ documents (FAISS/ChromaDB) and designed self-correcting agentic pipelines with LangGraph. Proficient in Python, LangChain, OpenAI API, and SQL; deepening expertise in computer vision and document layout analysis for structured extraction tasks. Independent learner with a track record of prototyping and shipping ML systems end-to-end — from research and experimentation to evaluation and deploymen
Skills & Technologies
Work Experience
AI/ML Engineer Intern
Architected and deployed end-to-end ML pipelines covering data ingestion, preprocessing, feature engineering, model training, and evaluation — boosting classification accuracy by 15% in production. Built production-grade RAG system using LangChain, FAISS, and ChromaDB; achieved 90%+ retrieval precision and reduced manual document lookup time by 40% across enterprise knowledge bases. Designed LangGraph multi-agent workflows with MCP Server integration — structured reasoning, dynamic tool orchestration, automated extraction — cutting task completion time by 45%. Developed and productionized NLP pipelines (sentiment analysis, text classification, NER) over 50,000+ records; deployed via FastAPI REST APIs with sub-second inference latency. Applied prompt engineering and context grounding to reduce LLM hallucinations by ~35%; improved downstream output reliability for business applications. Executed large-scale EDA using Python and SQL; statistical feature selection improved model F1-scores by 18% over baseline.
Data Analyst Intern
Analyzed marketing performance data across digital channels using Python and SQL, surfacing actionable insights that improved campaign ROI. Developed interactive dashboards and automated reporting pipelines, reducing manual effort and enabling real-time KPI visibility for leadership. Applied statistical analysis and data visualization to segment audiences and detect customer behavior trends, informing targeted campaign strategy. Translated business requirements into data-driven solutions using Pandas, NumPy, and Excel; presented findings to non-technical stakeholders.
Projects
Auto job apply ai agent
Architected an agentic AI system using LangGraph that autonomously searches for relevant job listings, tailors resume and cover letter content to job descriptions, and manages the application workflow end-to-end. • Integrated multi-step reasoning with tool-calling capabilities — enabling the agent to scrape job portals, extract requirements, and dynamically generate ATS-optimized application assets. • Implemented conditional branching and state-machine logic for robust agent orchestration, significantly reducing manual effort in the job application process
RAG Application — Document Q&A System
• Built a production-ready Retrieval-Augmented Generation (RAG) application using LangChain, OpenAI embeddings, and FAISS/ChromaDB to enable semantic question-answering over custom document sets. • Implemented advanced chunking strategies, embedding optimization, and retrieval pipelines — achieving high answer relevance with real-time response over user-uploaded documents. • Deployed with a Streamlit frontend and FastAPI backend, enabling non-technical users to query internal knowledge bases in natural language.
Education
Mba
Data science and machine learning
Bsc
Statistics