Ahmed S.

Key Skills

Software

Labelbox

Mercor

Data Annotation Tech

Top Subject Matter

Artificial Intelligence

Language Models

Multilingual Data

Top Data Types

Text

Image

Audio

Top Task Types

Text Generation

Evaluation Rating

Transcription

Function Calling

Object Detection

Question Answering

Red Teaming

Freelancer Overview

AI Trainer / Data Annotator with 2+ years of experience across platforms including Labelbox, Alignerr, Mercor, and DataAnnotation. Skilled in text labeling, prompt evaluation, and AI response rating, with a strong focus on quality, accuracy, and guideline adherence. Experienced in handling both English and Arabic data to improve model understanding and performance, with basic Python skills supporting structured and efficient workflows. Education includes Bachelor of Medicine and Bachelor of Surgery (MBBCh), Al-Azhar University (2025). Brings medical-level analytical thinking to AI training workflows, with strengths in evaluation, rating, linguistic analysis, and consistent quality assurance.

Labeling Experience

AI Trainer / Data Annotator

LabelboxText

Worked as an AI Trainer and Data Annotator on multiple platforms performing text labeling, prompt-based evaluation, and linguistic analysis tasks. Tasks included instruction following, text generation, and providing feedback in both English and Arabic. Maintained high performance standards and quality ratings, notably achieving a 4.8 rating in Labelbox. • Labeled and evaluated data on platforms such as Alignerr AI, DataAnnotation, Outlier, and Labelbox. • Focused on enhancing LLM and general AI model performance through contextual analysis. • Provided both qualitative and quantitative feedback to improve AI output accuracy. • Worked in a multilingual context, emphasizing English and Arabic data.

Worked as an AI Trainer and Data Annotator on multiple platforms performing text labeling, prompt-based evaluation, and linguistic analysis tasks. Tasks included instruction following, text generation, and providing feedback in both English and Arabic. Maintained high performance standards and quality ratings, notably achieving a 4.8 rating in Labelbox. • Labeled and evaluated data on platforms such as Alignerr AI, DataAnnotation, Outlier, and Labelbox. • Focused on enhancing LLM and general AI model performance through contextual analysis. • Provided both qualitative and quantitative feedback to improve AI output accuracy. • Worked in a multilingual context, emphasizing English and Arabic data.

2024 - Present

Education

Work History