Karim Ezz

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Evaluation Rating

Freelancer Overview

I am a detail-oriented software engineer with a strong background in computer science, algorithms, and data structures, which I leverage to ensure accuracy and efficiency in data labeling and AI training data workflows. My experience developing and optimizing scalable web applications has given me hands-on exposure to building robust, user-centric solutions and collaborating with cross-functional teams. I am proficient in Python, JavaScript, and SQL, and have worked extensively with modern tools and frameworks for both front-end and back-end development. My commitment to quality assurance, workflow optimization, and process improvement enables me to deliver reliable, high-quality labeled datasets essential for AI and machine learning projects. I am passionate about leveraging my technical skills to contribute to innovative AI solutions and continuously learning new technologies in the field.

Labeling Experience

Data Trainer & AI Data Annotator

Scale AITextEvaluation Rating

Served as a Data Trainer with an emphasis on validating AI data workflows. Worked on structured annotation and quality assurance of both structured and unstructured data to improve AI model performance. Conducted dataset cleaning, data annotation, and prompt testing for large language model (LLM) evaluation. • Performed structured and unstructured data labeling for model training and validation. • Developed and executed prompt testing and LLM evaluation strategies. • Ensured data quality through thorough data validation and cleaning processes. • Utilized Python and analytical tools to optimize data annotations and output review.

Served as a Data Trainer with an emphasis on validating AI data workflows. Worked on structured annotation and quality assurance of both structured and unstructured data to improve AI model performance. Conducted dataset cleaning, data annotation, and prompt testing for large language model (LLM) evaluation. • Performed structured and unstructured data labeling for model training and validation. • Developed and executed prompt testing and LLM evaluation strategies. • Ensured data quality through thorough data validation and cleaning processes. • Utilized Python and analytical tools to optimize data annotations and output review.

2023 - 2024

Education

Work History