Netraj Patil
@netrajpatil
Aspiring computer engineer building LLM workflows and autonomous agentic systems with production-ready Python.
What I'm looking for
I’m a Computer Engineering student with a strong interest in Artificial Intelligence—especially optimizing Large Language Model (LLM) workflows and building autonomous agentic systems. I enjoy turning research-grade ideas into practical, reliable software.
In my Data Science Intern role at Jio Platforms Limited (Reliance), I leveraged OCR technologies like docTR, Keras OCR, and pytesseract to build automated data extraction for complex document processing. I improved document comparison and validation using similarity score assessments, and supported real-time analysis by building a Flask RESTful API and data pipeline for production usage.
My projects reflect the same focus on LLM performance and system design. I built an LLM evaluation library (“LLM Jury”) for standardized scoring and benchmarking (including RAG and summarization), created “Glia,” a high-performance semantic caching library with a Watcher engine for automatic cache synchronization, and developed an autonomous AI assistant integrated with WhatsApp using LangChain/LangGraph, FastAPI, and external AI/search APIs.
Experience
Work history, roles, and key accomplishments
High-Performance Semantic Cache for RAG
Glia
Built a production-grade Python semantic caching library for LLM RAG that auto-synchronizes cache entries to prevent stale responses using CDC and polling.
LLM Jury
Project
Developed a Python library to evaluate Large Language Model (LLM) performance with standardized scoring and benchmarking for tasks like RAG and summarization.
Agentic AI Assistant Integrated with WhatsApp
Project
Built an autonomous WhatsApp AI assistant using a multi-tool agent architecture for tasks like calendar handling and web search.
Data Science Intern
Jio Platforms Limited
Built automated OCR-based data extraction pipelines and improved document comparison accuracy using similarity scoring and layout-aware modeling. Developed production-oriented Flask APIs and machine learning datasets using Hugging Face.
Education
Degrees, certifications, and relevant coursework
VIIT, Pune
Bachelor of Technology (B.Tech), Computer Engineering
Grade: CGPA: 8.83
Pursuing a B.Tech in Computer Engineering (3rd year). Maintains a CGPA of 8.83.
Chaitanya’s International School
Higher Secondary Certificate (HSC), Higher Secondary Education
Grade: Percentage: 81%; JEE Mains Percentile: 96.01
Completed Class 12 (HSC). Scored 81% and 96.01 percentile in JEE Mains.
Vidya Pratishthan’s Vinodkumar Gujar’s Bal Vikas Mandir
ICSE (Class 10), Secondary Education
Grade: Percentage: 92.83%
Completed Class 10 (ICSE). Scored 92.83%.
Availability
Location
Authorized to work in
Job categories
Skills
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