Constitution QA (RAG)
Retrieval-Augmented Generation system for grounded legal answers using embeddings + vector search.
AI/ML Engineer with 8× hackathon wins and strong delivery mindset. I love turning ideas into scalable solutions using GenAI, NLP, embeddings, and clean engineering.
Forward Deployed Engineer
B.Tech AIML (2025)
Focus
GenAI • ML • NLP
Strength
Shipping Products
Best Wins
Amazon • NITR • IITD
Not just projects — product-grade systems built with real engineering.
Retrieval-Augmented Generation system for grounded legal answers using embeddings + vector search.
AI content pipeline: story → scenes → prompts → output using async task processing.
Multi-model ML system with evaluation and performance comparison across classifiers.
Real-time face detection Flask app with dynamic bounding box visualization.
Fast execution under pressure. Strong proof of innovation + delivery.
A focused stack for building production-grade AI systems.
A quick timeline of how I’ve grown as an engineer and builder.
Built strong fundamentals in ML, deep learning, NLP, and software engineering.
Built retrieval-based AI systems, embeddings workflows, and prompt-driven pipelines.
Delivering real-world AI & software solutions by bridging business needs with technical implementation.
If you’re building an AI product, I’d love to contribute.