Usama S.

Hafiz M. U. is a dedicated Machine Learning Engineer with a focus on large language models (LLMs), retrieval-augmented generation (RAG) systems, and voice automation. Currently based at PixelEdge Solutions, he specializes in creating AI-powered systems that enhance operational efficiency by automating customer interactions and delivering human-like conversations through technologies like Twilio, OpenAI, and FastAPI. His work includes developing a voice AI using speech-to-text and text-to-speech technologies to manage customer support interactions autonomously, leveraging AWS for scalable deployments. Hafiz also excels in building RAG-based intelligent systems, utilizing LangChain and OpenAI for context-aware responses, and deploying these capabilities via modular REST APIs. His expertise extends to the fintech sector, where he constructs classical machine learning workflows for financial data processing and KPI forecasting, significantly streamlining reporting processes. Educationally, he combines his ongoing MSc in Data Science from FAST NUCES with prior qualifications from NED University, underscoring his rigorous academic background in electrical engineering and AI. Hafiz's technical prowess is exemplified by his proficiency in Python, LangChain, and FastAPI, making him a vital contributor to AI-driven innovation.