
Muhammad Furqan
Generative AI Engineer
Habilidades

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Experiência profissional
AI Engineer
Silicon Nexus • Período integral
Sep 2024 - Present • 1 yr 8 mos
At Silicon Nexus, I designed and deployed AI-driven backend systems with a focus on Natural Language Processing (NLP), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent voice integrations. My work centered on transforming complex AI research into practical, scalable, production-ready solutions across education, knowledge discovery, media, and technical diagnostics. I led the development of ParadeDeck AI, an AI-native platform for military podcasts featuring automated content ingestion, Whisper-based transcription, semantic search, and RAG-powered conversational chat. I integrated ElevenLabs voice synthesis to enable natural AI-generated audio clips and interactive content exploration. I developed Aurelia, an AI assistant for crane and remote control diagnostics that interprets manuals and error codes to deliver instant, context-aware troubleshooting steps, reducing downtime and improving operational safety. I worked on Brain Assistant, a conversational AI system acting as a centralized intelligence layer. It enables natural conversations, task execution, and knowledge retrieval by combining LLM reasoning with backend tools and APIs. In the education domain, I built MathWiz, an AI-powered learning platform that generates adaptive math questions, quizzes, and flashcards with a badge and achievement system for gamified learning. I also developed Akademus AI, an educational assistant that allows users to chat with PDFs, generate quizzes, flashcards, and summaries with page-cited responses, transforming static study material into interactive AI support. Additionally, I created SalahGPT, an Islamic AI assistant using RAG with Quran and Hadith references to deliver accurate, context-aware responses. Across all projects, I focused on blending strong backend engineering with applied AI to build reliable and impactful real-world systems.
Data Scientist
Knowledge Streams • Meio período
Mar 2023 - Oct 2024 • 1 yr 7 mos
At Knowledge Streams, I worked as a Data Scientist, focusing on data analysis, machine learning, and predictive modeling. I handled data cleaning, preprocessing, and visualization to extract meaningful insights from structured datasets and support data-driven decision making. I built and evaluated machine learning models for prediction and classification tasks using Python, Pandas, NumPy, and Scikit-learn. I also worked on feature engineering, model evaluation, and performance tuning to improve accuracy and reliability. Throughout my time there, I collaborated on real-world data projects, automated data workflows, and applied statistical techniques to solve practical problems. This experience strengthened my ability to translate raw data into actionable insights and laid a solid foundation for building production-ready AI systems.