Image Quality Scorer (Image Evaluation & Rating)
Rate image quality metrics and assess image-quality tools in a part-time contractor role, 20+ hours/week, $5–7/hr. Intermediate-level project for contributors with experience in image quality evaluation or annotation and fluent English.
Image & Video Annotation
$5–$7/hr
Compensation
Worldwide
Eligibility
Intermediate
Experience
Apr 15, 2026
Posted
Open worldwide
About OpenTrain
OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect contributors with projects that teach and shape AI systems — all remote, flexible, and accessible to people starting or growing careers in this fast-moving field.
About AI Training Work
AI training (also called data labeling or annotation) is the human work that helps AI learn: people provide examples, reviews, and ratings that guide model behavior. Image-quality scoring is a core part of this ecosystem — your judgments help researchers and engineers choose and calibrate metrics and tools that define image fidelity and usability.
The Role
This project asks contributors to evaluate images and rate image quality metrics and assessment tools. You will apply consistent judgment to images, follow project guidelines, and record evaluation ratings using the project's labeling interface (OTHER). This is a part-time contractor role with a minimum weekly commitment.
What You'll Do
- Review images and assign evaluation ratings according to project guidelines.
- Compare and score image quality metrics and assessment tool outputs.
- Follow instructions to ensure consistent, repeatable judgments across the dataset.
- Record ratings and any required notes in the provided labeling interface.
Requirements
- Availability: Minimum 20 hours per week.
- Experience: Previous experience with image quality evaluation or image annotation; intermediate level.
- Language: Fluent English proficiency required.
- Employment: Contract, part-time arrangement.
- Pay: Hourly, USD $5–7 per hour (PAY_PER_HOUR).
- Data & labels: Work is image-based with evaluation/rating label type.
- Tools: Project uses a custom/other labeling interface (listed as OTHER).
- Location: Worldwide — work remotely from any country.
Who Should Apply
Applied photographers, image annotators, QA reviewers, or anyone with hands-on experience judging image fidelity and artifacts will be a strong fit. If you can apply consistent subjective judgments and meet the weekly availability and language requirements, this project is a good match.