Mohamed Khaled

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Evaluation Rating

Segmentation

Text Generation

Freelancer Overview

I am an experienced AI Training Data contributor with a strong background in data labeling and annotation across various domains. My work has centered on preparing high-quality, accurate datasets that power machine learning models, with a deep focus on consistency, clarity, and adherence to project guidelines. I am skilled in handling large volumes of data, applying precise labeling techniques, and ensuring that outputs meet the quality standards required for effective AI training. What sets me apart is my commitment to detail and understanding of how well-labeled data directly impacts model performance. I have contributed to AI training projects that required linguistic, contextual, and analytical precision, developing a keen ability to identify nuances that improve dataset quality. My goal is always to deliver reliable training data that enables AI systems to perform with greater accuracy and efficiency.

Labeling Experience

AI Trainer – LLM Evaluator

LabelboxTextPrompt Response Writing SFT

Worked on AI Training and Evaluation by assessing and improving AI-generated responses to ensure accuracy, coherence, and contextual relevance. This involved reviewing outputs against specific guidelines, identifying errors or inconsistencies, and suggesting refinements to enhance overall quality. In addition, I contributed to data curation and prompt engineering, creating and refining inputs that improved model comprehension and output reliability. Through this work, I helped strengthen dataset integrity and optimize the performance of AI systems by aligning model responses more closely with human expectations.

Worked on AI Training and Evaluation by assessing and improving AI-generated responses to ensure accuracy, coherence, and contextual relevance. This involved reviewing outputs against specific guidelines, identifying errors or inconsistencies, and suggesting refinements to enhance overall quality. In addition, I contributed to data curation and prompt engineering, creating and refining inputs that improved model comprehension and output reliability. Through this work, I helped strengthen dataset integrity and optimize the performance of AI systems by aligning model responses more closely with human expectations.

2025 - 2025

Education

Work History