⚡ Devraj Pal (itzzdev09)

Full-Stack Software Engineer • Machine Learning Practitioner • Cloud & DevOps

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🖥️ $ whoami

devraj@workstation:~$ neofetch --profile

  OS: Linux / Windows Subsystem for Linux (WSL2)
  Kernel: Clean Architecture & Modular Microservices
  Uptime: 24/7 Problem Solver & Lifelong Learner
  
  Current Roles:
    - 🚀 Full-Stack Architect @ PrepArsenal (Next.js 15, Supabase, Python, LLM RAG)
    - 🔬 ML Systems Engineer (Explainable AI, PyTorch, CatBoost, SHAP)
  
  Tech Stack:
    - Frontend: Next.js 15, React 19, TypeScript, Tailwind CSS, Responsive UI
    - Backend: Node.js, Express, Python (Django, Flask, FastAPI), RESTful & GraphQL APIs
    - ML / Data: PyTorch, CatBoost, Scikit-Learn, Pandas, NumPy, Kafka, Redis
    - Cloud / DevOps: Docker, Kubernetes, Microsoft Azure, Linux, CI/CD Actions
  
  Engineering Core:
    - "Simplicity over complexity. Production-grade resilience over quick hacks."

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🚀 Interactive Tech Stack

Languages & Core Technologies

Frameworks, Libraries & Full-Stack

Machine Learning, Data & Caching

Cloud, DevOps & Engineering Tools

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🏆 Featured Flagship Repositories

🎯 PrepArsenal AI-Powered Exam Preparation & Adaptive Testing Engine Ingested 25,800+ deterministic PYQs across 9 high-stakes competitive exams. Item Response Theory (IRT) adaptive practice algorithms & ML trend forecasting. Built with Next.js 15, Supabase, TypeScript, and Python.	🛡️ XAI-PyTorch-IDS Explainable AI Network Intrusion Detection System Multi-class intrusion detection on imbalanced datasets using CatBoost with GPU acceleration. Model interpretability using SHAP feature importance & stratified downsampling. Built with PyTorch, CatBoost, SHAP, and Python.
🏡 Flat-AI Smart Real-Estate Marketplace & Valuation Platform End-to-end MERN platform for property discovery with intelligent recommendation engine. Integrated Django ML microservice for automated real-time property price estimation. Built with React, Node.js, Express, Django, and MongoDB.	📈 PrismPrice Dynamic Pricing Decision-Support Engine Real-time price elasticity modeling, demand curve estimation, and customer retention metrics. Automated price governance and causal revenue optimization. Built with Python, Kafka, Scikit-Learn, and Pandas.

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📊 System Architecture & Engineering Principles

  ┌─────────────────┐       ┌─────────────────┐       ┌─────────────────┐
  │  Next.js / SSR  │ ────> │ Node/Express API│ ────> │ PostgreSQL / DB │
  │ React & Tailwind│       │  Auth & Routing │       │ Supabase & RLS  │
  └─────────────────┘       └─────────────────┘       └─────────────────┘
           │                         │                         │
           ▼                         ▼                         ▼
  ┌─────────────────┐       ┌─────────────────┐       ┌─────────────────┐
  │ PyTorch / ML Svc│ <───> │ Redis & Caching │ <───> │ Docker & K8s CI │
  │  XAI & CatBoost │       │ Real-Time Queue │       │ Azure Deployment│
  └─────────────────┘       └─────────────────┘       └─────────────────┘

• 🧱 Architectural Cleanliness: Modular separation of concerns, DRY principles, type safety with TypeScript & Python type annotations.
• ⚡ Performance First: Edge caching, async database concurrency, vector indexing, and minimal bundle overhead.
• 🔒 Security Mindset: Strict Row-Level Security (RLS), JWT verification, input sanitization, and automated test suites.

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📬 Connect & Collaborate

Let's collaborate on impactful engineering projects, full-stack systems, or machine learning infrastructure!

_{Crafted with engineering precision by Devraj Pal (itzzdev09) • Powered by Open Source}