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 retrieval-based AI systems, embeddings workflows, and prompt-driven pipelines.
Built strong fundamentals in ML, deep learning, NLP, and software engineering.
Delivering real-world AI & software solutions by bridging business needs with technical implementation.
Building and deploying end to end working sites keeping the SEO, performance in mind.
If you’re building an AI product, I’d love to contribute.