Talal Muzaffar

Hey! I'm Talal, a machine learning engineer working on document AI, retrieval, and agentic systems.

ml lead at DOST AI

architected RAG @ 3.8M financial docs Multi-agent finance systems extraction · compliance · discrepancy detection

built with PyTorch LangChain LangGraph Google ADK MCP A2A FastAPI

recognised Google AI Booster — winning team, Madrid 2025

studied at FAST National University · Data Science Dean's List ’24–’25

I work in the parts of AI that don't make headlines — turning document chaos into queryable systems. At DOST AI I architected a RAG pipeline over 3.8M+ financial documents and built the multi-agent stack on top: extraction, compliance, discrepancy detection, vendor schema mapping. Full projects list here.

I fine-tune when curious: the Falcon-7B experiment hit 0.90 BERT on MICCAI using 4-bit QLoRA on a single T4. Outside of that, I follow open-source closely and try to ship something every month.

I co-authored Choices for Measuring Cognitive Function Digitally in LMICs at the American Epilepsy Society, and was selected for McKinsey Forward and Harvard's Crossroads.

Find me on

GitHub LinkedIn Résumé (PDF)

Or mail me at talalmuzaffar3@gmail.com