Muhammad Mustafa

AI Engineer & Software Developer

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About

Here is a little background

Hey 👋🏼 I'm Muhammad Mustafa, an AI Engineer currently working at Salik Labs in Pakistan. I completed my undergraduate degree in Electrical Engineering with a focus on Embedded Systems and AI. I have hands-on experience working across the AI stack, from developing machine learning models to building full-stack AI-powered applications. I'm passionate about leveraging technology to solve real-world problems and have experience with modern AI/ML frameworks, web development, and system optimization. When I'm not coding or working on AI projects, you'll probably find me deep into One Piece lore or dodging bosses in Elden Ring 🎮.

Experience

AI Engineer

Salik Labs
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Jun 2025 - Present

  • Lead development and deployment of machine learning models for production environments, ensuring scalability and reliability
  • Architect and build AI-powered applications using cutting-edge frameworks including TensorFlow, PyTorch, and modern web technologies
  • Design and implement end-to-end AI solutions from data preprocessing to model deployment and monitoring
  • Research and implement state-of-the-art AI/ML algorithms to solve complex business problems and drive innovation

Junior AI Developer

AI Data House (SMC-PVT) LTD
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Feb 2025 - Apr 2025

  • Developed a Handball Game statistics program using Computer Vision (CV) applications for real-time sports analytics
  • Created, tested and fine-tuned various Large Language Models (LLMs) for diverse chatbot applications
  • Integrated machine learning backends into websites to enhance functionality and user experience
  • Delivered cutting-edge AI solutions for sports analytics and web applications in an on-site environment
  • Collaborated with cross-functional teams to implement AI-driven features and optimize model performance

Research Assistant

Robotics and Machine Intelligence (ROMI) Lab
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Feb 2024 - May 2025

  • Working on a research-based project in collaboration with professors at Tennessee Tech, USA
  • Focused on detecting Trojans in IP (Intellectual Property) and at the SOC (System on Chip) development stage
  • Utilizing Graph Neural Networks (GNNs) for Trojan detection by converting Verilog code into graph structures
  • Developing innovative approaches that capture hierarchical structure of IP modules through graph representations
  • Implementing advanced machine learning techniques for cybersecurity applications in hardware design

Deep Learning Research Intern

Deep Learning Lab, National Centre of Artificial Intelligence (NCAI)
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Jun 2023 - Feb 2024

  • Implemented transformer models on edge devices using FPGA to reduce computation and enable local execution
  • Focused on optimizing transformer model performance for deployment on resource-constrained edge devices
  • Conducted research on efficient deep learning architectures for embedded systems and IoT applications
  • Collaborated with research teams to develop novel approaches for model compression and acceleration
  • Contributed to advancing the field of edge AI through practical implementation and performance optimization

Skills

Hover over a skill to see its name

Python

Python

TensorFlow

TensorFlow

PyTorch

PyTorch

AWS

AWS

Google Cloud

Google Cloud

JavaScript

JavaScript

React

React

Data Science

Data Science

Docker

Docker

Git

Git

SQL

SQL

Embedded Systems

Embedded Systems

Projects

Contract Summary AI

Contract Summary AI

Built a full-stack application using Flask and React to summarize and analyze UK construction contracts. Implemented RAG with LangChain, GPT-4o, and ChromaDB for document processing and conversational AI.

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LangGraph Chatbot Workflow

LangGraph Chatbot Workflow

Developed an interactive chatbot system leveraging LangGraph, LangChain, and Local LLM model, deployed on Render. Built conversational flows with real-time WebSocket communication and responsive frontend design.

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Hospital Website

Hospital Website

Developed a fully functional hospital website with patient ticketing system and expense database using MERN stack, deployed on Firebase. Features responsive design and integrated patient management.

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Federated Learning Movie Recommendation System

Federated Learning Movie Recommendation System

Developed a privacy-preserving movie recommendation system using Federated Learning and Collaborative Filtering on MovieLens 20M dataset. Addressed scalability and cold start challenges.

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4-Bit Microprocessor

4-Bit Microprocessor

Designed a simple 4-bit microprocessor for basic arithmetic and control operations. Includes 8 instructions and 16 4-bit registers, capable of arithmetic, branching, and looping. Simulated in Proteus.

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Reinforcement Learning Mario Agent

Reinforcement Learning Mario Agent

Trained a Mario agent using various reinforcement learning algorithms including DQNN, CNN, and MobileNet-V2. Achieved optimal results with Deep Q-Neural Network implementation.

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Contact

I have got just what you need. Let's talk

+92 309 3243363

muhammadmustafakhakwani@gmail.com

Islamabad, Pakistan