ML Engineer specializing in fine-tuning transformers, edge AI deployment, and RAG pipelines. Currently exploring agentic AI and vector databases.
Hey, I'm Zayed :), an AI & Data Science student from Mumbai who's genuinely obsessed with building things that work, not just things that demo well.
I got into AI because I wanted to understand how machines actually learn, not just call an API and call it a day. That curiosity pushed me toward fine-tuning transformers, building RAG systems from scratch, and deploying models on edge hardware like Raspberry Pi real constraints, real tradeoffs.
Building multi-step AI agents with LangGraph that can reason, plan, and act autonomously across tasks.
Going deeper into Pinecone and Weaviate for production-grade semantic search at scale.
Learning MLflow and Weights & Biases to bring proper experiment tracking into my ML workflow.
Documenting what I build — because the best engineers can explain their systems as well as they code them.
Production-ready Retrieval-Augmented Generation system enabling multi-document querying across PDFs with automatic source citations. Processes 27-page documents with sub-second response times and 90%+ answer relevance.
Fine-tuned GPT-2 on Shakespeare's sonnets to generate real-time poetry with preserved meter and rhyme schemes. Engineered custom loss functions optimizing for poetic structure.
Contributed to an ensemble CNN (Xception + InceptionV3) for road condition monitoring. Deployed on Raspberry Pi for edge inference, demonstrating low-cost AI solution for infrastructure monitoring. My contributions focused on model optimization and edge deployment.