---
title: "Chakreshkumar Vulli - Artificial intelligence and machine Learning in Vadodara | Tal"
description: "Meet Chakreshkumar Vulli, AI Engineer | Building AI Agents & Multi-Agent Systems | LangChain • RAG • LLMs • FastAPI • n8n | Open to AI Engineer Internships based in Vadodara. AI stack includes claude, cursor, and hugging face. Explore public work links including github."
image: "https://tal.club/meet/chakresh-kumar-vulli/share-image"
---

# Chakreshkumar Vulli on Tal

## Headline

AI Engineer \| Building AI Agents & Multi\-Agent Systems \| LangChain • RAG • LLMs • FastAPI • n8n \| Open to AI Engineer Internships

## About

I'm an AI Engineer passionate about building production\-ready Generative AI systems that solve real business problems\. My expertise includes: • AI Agents & Multi\-Agent Systems • Retrieval\-Augmented Generation \(RAG\) • LangChain, LangGraph & Vector Databases • Workflow Automation \(n8n, Make, Zapier\) • FastAPI, Python & Scalable AI Backends • LLM Applications & AI Automation I've built AI\-powered solutions including: ✓ Resume Screening System ✓ AI Research Assistant ✓ RAG Chatbots ✓ Workflow Automation Agents ✓ Document Intelligence Systems Currently seeking: • AI Engineer Internships • GenAI/LLM Roles • Freelance AI Development • Startup Collaborations Always excited to connect with builders creating impactful AI products\.

## Location

Vadodara

## AI stack

claude

cursor

hugging face

langgraph

langsmith

n8n

## Work experience

Artificial intelligence and machine Learning at Elevate Labs, Sep 2025 \- Oct 2025 · 1 mo, Remote, I worked on several machine learning and deep learning tasks during my internship and learned how real projects are handled from start to finish\. • Completed 6 mini projects, including ML, NLP, and computer vision assignments\. • Improved my skills in data cleaning, data handling, feature engineering, and managing different types of datasets\. • Worked on building and improving different models: – Random Forest accuracy: 88 percent – SVM accuracy improved from 79 percent to 86 percent – CNN model accuracy on image data: 92 percent • Learned how to use evaluation metrics like accuracy, precision, recall, F1\-score, and confusion matrix\. • Completed a Face Mask Detection Project using deep learning and OpenCV to check if a person is wearing a mask\. – Achieved 94 percent accuracy and good real\-time performance\. Overall, this internship helped me understand AIML concepts better, work with real data, and build models with better accuracy and performance\.

Ai Builder at HarvestHands, Jul 2025 \- Nov 2025 · 5 mos, Gujarat, India, • Built RAG\-powered chat systems using LangChain, FAISS, and Pinecone • Developed intelligent agent workflows using LangGraph \+ MCP • Created content simplifying ML concepts for \+3,600 LinkedIn followers

## Education

Bachelor of Technology \- BTech, Artificial Intelligence, Parul University

Inter, Narayana Junior College \- India

## Public links

- github: https://github\.com/Chakresh7

[View the original profile](https://tal.club/meet/chakresh-kumar-vulli)

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