Muneeb Ahmed

AI/ML Engineer

GitHub | LinkedIn

About

Highly accomplished AI/ML Engineer with over 2 years of experience in designing, optimizing, and deploying production-ready AI/ML models across diverse platforms including CoreML, ONNX, and TensorRT. Proven expertise spans computer vision, deep learning, and large language models, evidenced by a 40% improvement in training efficiency and 65% reduction in inference costs while consistently maintaining 95%+ accuracy. Adept at developing scalable ML backends and real-time AI decision systems for mission-critical applications.

Work Experience

AI/ML Engineer

Freelance AI/ML Engineer

Nov 2022 - Present

Provided expert AI/ML engineering services, specializing in model fine-tuning, NLP pipeline development, and cross-platform AI solution deployment for diverse clients.

  • Fine-tuned 20+ deep learning models (GPT-4, Llama, Falcon) using PyTorch and TensorFlow, achieving 90% accuracy on domain-specific tasks while reducing inference costs by 50%.
  • Implemented advanced NLP pipelines with transformer architectures for entity extraction, sentiment analysis, and intent classification, maintaining 98% uptime for mission-critical business operations.
  • Developed cross-platform AI solutions deployed on Mac, Windows, and mobile platforms, optimizing models using ONNX and CoreML for edge deployment with 65% cost reduction.
  • Built computer vision systems processing 1000+ daily images with 92% accuracy, implementing CNN architectures with custom data augmentation and real-time inference optimization.

AI Developer

TekRevol

Mar 2024 - Apr 2025

Led the design and implementation of advanced AI solutions, focusing on LLM fine-tuning and scalable ML backend development for production environments.

  • Designed and implemented a localized fine-tuning pipeline for LLMs using PyTorch, boosting training efficiency by 40% and enabling secure on-premises model development.
  • Integrated Unsloth optimization framework to enhance GPU usage efficiency by 4x, enabling 100x faster LORA training and supporting 7B parameter model fine-tuning on limited hardware resources.
  • Developed autonomous AI agents with TensorFlow-based models for market research, achieving 85% accuracy in product potential analysis and customer sentiment classification.
  • Built a scalable ML backend using FastAPI with optimized model serving infrastructure, implementing professional MLOps practices for production deployment.

AI Researcher

National Center of Artificial Intelligence (NCAI)

Sep 2024 - Nov 2024

Conducted research and development in real-time AI decision systems and optimized deep learning model deployment for edge devices.

  • Designed real-time AI decision systems using TensorFlow, reducing model inference latency from 500ms to 75ms through advanced optimization techniques and hardware acceleration.
  • Implemented comprehensive model monitoring frameworks with automated QA protocols, achieving 99.9% system reliability for production AI deployments.
  • Optimized deep learning model deployment pipelines for edge devices using TensorRT and quantization techniques, reducing inference costs by 65% while maintaining 95% accuracy.
  • Developed a parking space detection system using convolutional neural networks for LiDAR scan analysis, implementing high-precision real-time classification.

Education

Computer Information & Systems Engineering

NED University of Engineering and Technology

3.85/4.00

Sep 2022

Courses

  • Machine Learning
  • AI Architecture
  • Computer Vision
  • Automated Systems
  • Vehicle detection and tracking using YOLOv8 and DeepSORT for real-time traffic monitoring

Certificates

Generative AI with Large Language Models

DeepLearning.AI

Jan 2024

Fine-tuning Large Language Models

DeepLearning.AI

Jan 2024

Projects

Vehicle Re-Identification System

Sep 2022 - Nov 2024

Developed a real-time vehicle re-identification system for traffic monitoring.

Brain Tumor Segmentation

Sep 2022 - Nov 2024

Developed an AI model for accurate brain tumor segmentation from MRI images.

Real-time Gesture Recognition

Sep 2022 - Nov 2024

Built a robust system for real-time gesture recognition with optimized performance for mobile devices.

Image Captioning with Transformers

Sep 2022 - Nov 2024

Designed a transformer-based architecture for high-performance image-to-text generation.

Brain-Controlled Interface

Sep 2022 - Nov 2024

Applied on-device AI for EEG signal processing to enable assistive technology.

Awards

First Prize, EMU INVENT 2024

EMU INVENT

Jan 2024

Awarded for AI-integrated Brain-Controlled Wheelchair using on-device ML models.

MAAJEE Scholarship Recipient 2023

MAAJEE

Jan 2023

Awarded for academic excellence in AI/ML coursework.

Languages

English

Skills

AI/ML Frameworks

  • TensorFlow
  • PyTorch
  • Keras
  • Scikit-learn
  • OpenCV

Model Optimization

  • ONNX Runtime
  • TensorRT
  • CoreML
  • Quantization
  • Pruning
  • Unsloth
  • PEFT
  • LoRA

Deep Learning

  • CNNs
  • RNNs
  • Transformers
  • YOLO
  • U-Net
  • ResNet
  • Attention Mechanisms
  • LLMs
  • Fine-tuning

Computer Vision

  • Object Detection
  • Segmentation
  • Tracking
  • Feature Extraction
  • LiDAR Scan Analysis
  • Data Augmentation

Programming Languages

  • Python
  • C++
  • CUDA
  • JavaScript
  • SQL

Cloud & Deployment

  • AWS
  • GCP
  • Azure
  • MLOps
  • CI/CD
  • Model Monitoring
  • Production Deployment
  • Hardware Acceleration

Problem Solving

  • System Reliability
  • Performance Optimization
  • Real-time Systems

Platforms

  • Mac
  • Windows
  • Linux
  • Mobile (iOS/Android)
  • Edge Devices

Tools & Libraries

  • HuggingFace
  • Docker
  • Git
  • Jupyter
  • FastAPI