I'm Ranjit N, an aspiring AI/ML engineer currently pursuing an Integrated M.Sc. in Data Science. I specialize in building intelligent systems that transition seamlessly from concept to production. My work spans:

• LLM-Powered Agents: Multi-agent frameworks using LangChain and vector search.
• Production ML: Real-world pipelines with monitoring, retraining, and secure cloud deployment.
• Full-Stack AI Applications: FastAPI + Next.js + Tailwind CSS — from model to UI.
• Deep Learning from Scratch: Transformers, autoencoders, hybrid loss functions — built the hard way.

• 🌍 Turning multi-agent LLM demos into useful real-world tools
• 🧠 Researching factual consistency in radiology report summarization with RE, NER & contrastive learning
• ⚙️ Learning proper software engineering practices: modular Python, CI/CD, observability, logging
• 💡 Experimenting with open-weight LLMs, LoRA fine-tuning, RAG pipelines
• 🧱 Exploring backend engineering deeply and picking up Go (Golang) to build scalable, robust APIs

• I believe in debuggable AI — if you can't log, trace, or evaluate it, it’s just a toy.
• Every model I build is paired with deployment, monitoring, and a frontend.
• I avoid overengineering early. MVP > Complexity.
• I like breaking things down and building them from scratch when needed — especially when learning.

I’m actively looking for:

• AI/ML engineering internships (especially GenAI, MLOps, or backend-heavy)
• Research collabs in medical NLP or LLM reliability
• OSS projects in LangChain, vector DBs, or multi-agent frameworks

• 📧 Email: ranjitnagaraj2131@gmail.com
• 🧠 Twitter (X): @Ranjit_AI
• 💼 LinkedIn: linkedin.com/in/ranjit-n

🧪 "I don't just train models. I make them work in production."