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E
Ebele Onyia

Ebele Onyia

AI Data Labeling & Image Edit Evaluation Contractor

USA flagLoganville, Usa
$60.00/hrIntermediate

Key Skills

Software

No software listed

Top Subject Matter

AI Image Editing and Evaluation
E-commerce - Product Categorization
Product Management

Top Data Types

ImageImage
TextText

Top Task Types

Evaluation/RatingEvaluation/Rating

Freelancer Overview

As an AI Data Labeling and Image Edit Evaluation Contractor, I evaluate AI-generated image edits by comparing the original image, the user’s prompt, and the edited output. My work focuses on assessing whether the edit follows instructions, maintains visual quality and realism, preserves object consistency, and avoids issues like distortions, hallucinated objects, artifacts, or style mismatches. Through structured labels and concise written feedback, I help identify patterns in where the model succeeds or fails. This feedback supports improvements to AI image-editing systems by making subjective visual judgments more consistent, measurable, and useful for model training and evaluation.

IntermediateEnglishFrench

Labeling Experience

AI Data Labeling & Image Edit Evaluation Contractor

Image
As an AI Data Labeling & Image Edit Evaluation Contractor, I evaluated AI-generated image edits for prompt adherence, visual quality, realism, object consistency, and artifact detection. I produced structured labels and detailed written feedback to improve model performance and reliability. My work involved consistent annotation decisions and concise rationales to facilitate the identification of recurring failure patterns. • Assessed edited images for missed edits, hallucinations, distortions, and safety issues. • Provided clear, structured feedback supporting model development. • Developed expertise in annotation and quality assurance workflows. • Enhanced image-editing evaluation standards and best practices.

As an AI Data Labeling & Image Edit Evaluation Contractor, I evaluated AI-generated image edits for prompt adherence, visual quality, realism, object consistency, and artifact detection. I produced structured labels and detailed written feedback to improve model performance and reliability. My work involved consistent annotation decisions and concise rationales to facilitate the identification of recurring failure patterns. • Assessed edited images for missed edits, hallucinations, distortions, and safety issues. • Provided clear, structured feedback supporting model development. • Developed expertise in annotation and quality assurance workflows. • Enhanced image-editing evaluation standards and best practices.

2025 - Present

Education

U

University of Notre Dame

Bachelor of Arts and Letters, Computer Science

Bachelor of Arts and Letters
2023

Work History

D

Deloitte

Product Manager Intern

New York
2024 - Present
V

Vennote Technologies Inc

Software Quality Assurance Tester Intern

Lagos
2023 - 2023