Passionate about building production-ready backend systems, AI-powered applications, semantic retrieval platforms, and scalable distributed services.

• 🎓 B.Tech Computer Science Engineering student at KMIT (2023–2027)

• 💻 Backend-focused engineer with hands-on experience building:

  • Scalable REST APIs
  • LLM-powered applications
  • Semantic search systems
  • Real-time inference pipelines
  • Distributed backend services

• ⚡ Strong interest in:

  • Backend Engineering
  • Applied AI
  • Distributed Systems
  • AI Infrastructure
  • Retrieval-Augmented Generation (RAG)
  • System Design

• 🧠 Currently learning:

  • Advanced Backend Architecture
  • PostgreSQL Internals
  • Distributed Caching
  • AI Infrastructure & MLOps

• LangChain
• Vector Databases
• Semantic Search
• NLP
• Transformers
• Retrieval-Augmented Generation (RAG)

🔹 Built a scalable AI-driven platform for evaluating startup ideas using LLM workflows, semantic retrieval, and intelligent scoring systems.

• Implemented semantic search using Vector Databases + LangChain
• Designed scalable backend APIs using FastAPI & Express.js
• Improved API performance using Redis caching & optimized workflows
• Built modular architecture supporting concurrent user interactions
• Integrated JWT authentication and real-time AI responses

FastAPI Node.js MongoDB Redis LangChain PineconeDB OpenAI API

🔗 GitHub: https://github.com/mad674/startupideavalidator

🔹 Developed a financial QA system combining neural retrieval with symbolic reasoning for interpretable predictions.

• Built BERT-based retrieval pipeline

• Implemented LSTM-based program generator

• Designed symbolic execution workflows

• Engineered end-to-end ML pipelines:

  • preprocessing
  • training
  • evaluation
  • inference

• Achieved ~80% prediction accuracy

PyTorch FastAPI Firebase NLP LSTM

🔗 GitHub: https://github.com/mad674/qa

🔹 Built a real-time sketch-to-image generation platform using Generative Adversarial Networks.

• Implemented Pix2Pix GAN architecture
• Developed real-time inference pipeline
• Improved image generation quality through iterative optimization
• Built scalable client-server architecture

TensorFlow Flask Node.js MongoDB

🔗 GitHub: https://github.com/mad674/mlmodel

• Backend Engineering
• Distributed Systems
• AI Infrastructure
• LLM Applications
• System Design
• Semantic Retrieval
• Scalable APIs
• High-Performance Backend Systems

• Solved 500+ DSA problems
• Built multiple production-oriented AI systems
• Secured a Top Team Award at KMIT Project Expo
• Participated in national-level hackathons

📧 Email: madhavmeruva690@gmail.com 💻 LeetCode: https://leetcode.com/123mad

Building scalable systems and intelligent applications through backend engineering and applied AI.