🎓 M.Tech in Applied AI | 🔧 Embedded Systems Enthusiast | 🤖 AI Systems Builder

I work at the intersection of low-level systems and intelligent software, building solutions that connect hardware, data, and machine learning into practical, deployable systems.

• 🧠 Build AI-powered systems (RAG pipelines, NLP datasets, model evaluation)
• ⚙️ Work with embedded + system-level programming (C/C++, debugging, memory, toolchains)
• 🔍 Explore MLOps workflows — from development to deployment
• 🎙️ Experiment with voice assistants & local LLM integrations (Ollama-based systems)

• 📌 Edge AI Systems Designing intelligent pipelines for real-world deployment

• 📌 RAG + Local LLMs Building document-aware Q&A systems using PDFs + OCR

• 📌 MLOps & Workflow Automation CI/CD for ML, validation pipelines, and reproducibility

Python • C • C++ • SQL • Embedded C

• NLP (Q&A generation, dataset creation)
• Retrieval-Augmented Generation (RAG)
• Model evaluation & fine-tuning
• Signal processing basics

• Linux (Ubuntu, WSL debugging)
• GDB, OpenOCD
• Git & GitHub
• Ollama (local LLM deployment)

• Memory management (heap/stack/data)
• Data structures & algorithms
• CI/CD for ML systems
• Feature pipelines & validation

• 🧠 RAG-based PDF QA System → Query structured knowledge from documents

• 🤖 Local LLM Assistant (Jarvis-style) → Voice-enabled AI assistant with dynamic responses

• 📊 NLP Dataset Generator → Adaptive Q&A generation from OCR + PDFs

• ⚙️ Custom C++ STL-like Implementations → Rebuilding data structures from scratch

• Advanced MLOps pipelines (TFX, orchestration, monitoring)
• Efficient Edge AI deployment strategies
• System design for AI + Embedded integration

• 💬 Ask me about: AI Systems • Embedded Debugging • RAG Pipelines • MLOps

• 📫 LinkedIn: Click Here

Build systems that don’t just work — but scale, adapt, and explain themselves.