Osama A.

Key Skills

Software

OpenCV AI Kit (OAK)

Roboflow

Other

Data Annotation Tech

Labelbox

LabelImg

Scale AI

Datature

Datasaur

Dataturk

Datumbox

Top Subject Matter

Generative AI and Large Language Models

Top Data Types

Text

Image

Document

Top Task Types

Fine-tuning

Text Generation

Data Collection

Object Detection

Classification

Text Summarization

Bounding Box

Computer Programming/Coding

Freelancer Overview

Participant, Generative AI Training Program. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, Fayoum University (2022). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.

Labeling Experience

Large Language Model (LLM) Fine-Tuning & RAG

TextText Generation

Building llms (chatbots) , Building Rag systems , prepared specialized datasets for fine-tuning Large Language Models (specifically Llama-3 and JAIS) to create a production-ready AI agent. My work involved cleaning and formatting text data for Supervised Fine-Tuning (SFT) and building Retrieval-Augmented Generation (RAG) pipelines. I focused on ensuring the model could handle localized language nuances for an agricultural auction platform.

2026 - 2026

Participant, Generative AI Training Program

TextFine-tuning

Participated in a Generative AI Training Program focused on studying large language models and generative AI concepts. Developed hands-on projects with practical implementation of AI training. Engaged in activities directly related to AI model improvement and evaluation. • Studied and experimented with large language models for generative applications. • Implemented practical AI projects supporting model fine-tuning workflows. • Practiced prompt engineering and model output review for quality control. • Enhanced skills in evaluating and refining generative AI responses.

2025 - 2026

Deep Learning Pipeline for Image Classification and Segmentation

ImageSegmentation

Developed and trained various neural network architectures, including CNNs and U-Net, for image-related tasks. Implemented transfer learning techniques to enhance classification accuracy and optimize training time. Worked on detecting human emotions from facial images and recognizing handwritten digits (MNIST). Applied deep learning techniques to identify and separate objects within complex images.

2025 - 2025

Machine Learning End-to-End Projects (Business & Customer Analytics)

DocumentClassification

Performed comprehensive data cleaning, preprocessing, and exploratory data analysis (EDA) on real-world datasets. Built complete machine learning pipelines from data preparation to model deployment. Developed predictive models for customer behavior and business insights to support decision-making processes. Utilized Python libraries such as Pandas, NumPy, and Scikit-learn to evaluate and improve model performance.

2024 - 2025

Education

Work History