Hi, I'm

Pradeep Yadav

Full-Stack Developer | AI Engineer

Aspiring AI Engineer focused on Generative AI and RAG-based systems, building AI-powered applications that transform complex data into meaningful solutions.

🤖 AI/ML
FastAPI
🐍 Python
🔍 RAG Systems

About Me

I am a recent B.Tech graduate in Computer Science and Engineering from the Indore Institute of Science and Technology (IIST), specializing in Generative AI and software development. I focus on building robust, AI-driven applications to solve real-world automation and data retrieval challenges.

During my internship as a Generative AI Intern, I engineered RAG-based AI chatbots using Python and LangChain. I developed vector ingestion pipelines, search mechanisms, and conversation memory architectures to retrieve relevant context and generate accurate, grounded LLM responses.

I enjoy exploring state-of-the-art AI tech, refining backend architectures, and continuously learning to build scalable and efficient software solutions.

💻

Skills & Expertise

🤖

AI & Machine Learning

  • PyTorch
  • LangChain
  • NLP
  • LangGraph
⚙️

Backend Development

  • Python
  • FastAPI
  • PostgreSQL
  • MongoDB
🎨

Frontend Development

  • HTML5 & CSS3
  • JavaScript
  • React
🛠️

Tools & Technologies

  • Git & GitHub
  • Docker
  • DSA
  • AWS/Cloud

Experience

💼
July 2025 - October 2025

Generative AI Intern

Mindpath Tech Pvt Ltd, Indore

Worked as a Generative AI Intern at Mindpath Tech Pvt Ltd, where I engineered AI-powered chatbot prototypes using LangChain and OpenAI models. Implemented RAG-based document retrieval to generate context-aware responses from client-provided documents in a controlled demo environment.

Key Achievements:
  • Engineered custom RAG pipelines utilizing OpenAI embeddings and vector stores (pgvector/PostgreSQL and MongoDB Atlas), optimizing information retrieval precision.
  • Built and deployed a secure, interactive demonstration web interface using FastAPI and Streamlit for client testing and feedback.
  • Implemented sliding-window conversation memory and semantic search routing to improve conversational contextual depth and consistency.
  • Optimized prompt templates and system directives, reducing hallucination rates and raising relevance scores by refining input context bounds.
  • Conducted database benchmarking to evaluate vector search latency and response speeds under concurrent client loads.
Python FastAPI PostgreSQL Git LangChain LangGraph MongoDB Streamlit LLM

Projects

Python Streamlit ChromaDB LLM

Multi-Model RAG System

Engineered a high-performance RAG pipeline leveraging Gemini-1.5-Flash, Sentence Transformer embeddings, and ChromaDB. Optimized context relevance using semantic parent-child chunking, reducing context payload size and model query costs.

NLP Python Streamlit LLM

AI-Powered Resume Analyzer

Developed an ATS-aligned resume analyzer utilizing Python, NLP, and Gemini API. The system parses uploaded PDF resumes, matches skills against target job descriptions, computes similarity scores, and outputs structured suggestions for keyword optimization.

ML NLP Python Streamlit

Fake News Detection System

Built a supervised machine learning system to classify articles as real or fake. Trained an ensemble classifier on TF-IDF features extracted from text bodies, deploying the trained model via a FastAPI backend and a Streamlit front-end interface.

Django Python Bootstrap SQLite Razorpay API AccuWeather API

TravelBuddy

Designed a travel planning portal utilizing Django, SQLite, and the Gemini API. Integrates AccuWeather API and Razorpay for booking workflows, delivering dynamically generated, weather-aware travel itineraries tailored to user budgets.

Resume

View my complete resume or download the PDF version

Contact Me

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