Mahmoud Gamal

Key Skills

Software

Snorkel AI

Labelbox

Roboflow

Top Subject Matter

Python Programming

AI Code Evaluation

General AI Text Generation and Evaluation

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Computer Programming/Coding

Prompt + Response Writing (SFT)

Data Collection

Function Calling

Transcription

Evaluation/Rating

Text Generation

Object Detection

Bounding Box

Classification

Segmentation

Point/Key Point

Question Answering

Text Summarization

Red Teaming

Fine-tuning

Entity (NER) Classification

Freelancer Overview

Data Annotator. Core strengths include Snorkel AI, N, and A. Education includes Bachelor of Science, Modern Sciences and Arts (MSA) University (2026) and High School Diploma, Saleh al-Shehab Secondary School (2021). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Data Annotator at Outlier

LabelboxText

As a Data Annotator at Outlier, I was responsible for evaluating complex text outputs generated by AI models for accuracy, safety, and helpfulness. I conducted in-depth research and rewrote AI responses to create high-quality baselines for model training. This included analyzing, editing, and ranking model outputs per detailed guidelines. • Assessed factual accuracy, narrative flow, and bias in AI-generated texts. • Conducted side-by-side comparisons and provided written justifications for ranking outputs. • Edited and enhanced AI responses to ensure they meet project criteria. • Applied rigorous safety and helpfulness rubrics to annotated content.

As a Data Annotator at Outlier, I was responsible for evaluating complex text outputs generated by AI models for accuracy, safety, and helpfulness. I conducted in-depth research and rewrote AI responses to create high-quality baselines for model training. This included analyzing, editing, and ranking model outputs per detailed guidelines. • Assessed factual accuracy, narrative flow, and bias in AI-generated texts. • Conducted side-by-side comparisons and provided written justifications for ranking outputs. • Edited and enhanced AI responses to ensure they meet project criteria. • Applied rigorous safety and helpfulness rubrics to annotated content.

2026 - Present

Data Annotator at Alignerr

Snorkel AI

In this role, I participated in general AI training, code evaluation, and prompt engineering, focusing on technical outputs produced by machine learning models. My responsibilities included leveraging expertise in Python to assess, correct, and provide comprehensive feedback on AI-generated code snippets. I consistently ensured the technical validity and improved algorithmic efficiency of outputs for enhanced model performance. • Evaluated and annotated Python code for logical correctness. • Corrected AI-generated errors in code structure and logic. • Collaborated with technical teams to establish quality standards. • Contributed to model improvement through targeted feedback.

In this role, I participated in general AI training, code evaluation, and prompt engineering, focusing on technical outputs produced by machine learning models. My responsibilities included leveraging expertise in Python to assess, correct, and provide comprehensive feedback on AI-generated code snippets. I consistently ensured the technical validity and improved algorithmic efficiency of outputs for enhanced model performance. • Evaluated and annotated Python code for logical correctness. • Corrected AI-generated errors in code structure and logic. • Collaborated with technical teams to establish quality standards. • Contributed to model improvement through targeted feedback.

2026 - Present

Education

Work History