Image Annotation Quality Control Specialist

About OpenTrain AI

OpenTrain AI is the #1 platform for building careers in AI training and data labeling. We connect contributors with projects that shape how state-of-the-art AI systems behave and provide tools, training, and feedback so you can grow your skillset in this fast-growing field.

Why AI training matters and why people do this work

AI training (also called data labeling or annotation) is the human work behind every modern AI system: people create, correct, and evaluate examples that models learn from. Contributors commonly work 100% remotely, choose flexible hours, and move into more specialized, higher-paying projects as they gain experience.

• Remote, flexible work that fits around studies or other jobs
• Accessible entry points—many projects need attention to detail more than prior experience
• Direct impact on how production AI systems perform and behave

The role

OpenTrain AI is hiring an Image Annotation Quality Control Specialist to review an 8,000-frame dataset captured from refinery footage. Most frames were auto-annotated; your job is to verify those annotations, correct errors, and add missing labels where needed. The model performs reliably on clear frames, so you will focus on borderline, cluttered, or low-visibility frames.

You will work with CVAT to inspect and edit bounding boxes and classification labels. Sample frames are available for review at: https://mega.nz/folder/wZQjHDjR#8EQ7FCugT_o3oj1aNtiarQ

• Data type: images (frames from refinery footage)
• Label types: bounding box and classification
• Labeling software: CVAT
• Dataset size: ~8,000 frames

What you'll do day-to-day

Your primary responsibility is quality control: verify auto-annotations, correct bounding boxes, assign or confirm class labels, and add annotations when the model missed objects. You will follow project guidelines and log edge cases or recurring model mistakes so the annotation workflow improves over time.

• Review auto-annotated frames and accept, correct, or add annotations in CVAT
• Adjust bounding boxes for accuracy and ensure class labels match guidelines
• Flag ambiguous or unclear frames and document common error patterns
• Work with the OpenTrain AI team to clarify annotation rules and edge cases

Requirements

We need contributors who combine careful visual inspection with practical annotation skills. This is an intermediate-level task: you should be comfortable making judgment calls on borderline frames and documenting inconsistencies.

• Strong attention to detail in quality control
• Experience reviewing and correcting auto-annotations (image bounding boxes and classification)
• Fluent English proficiency for reading guidelines and writing clear notes
• Ability to work 20+ hours per week
• Familiarity with CVAT or similar annotation tools is preferred

Who should apply

Apply if you have practical experience with image annotation, especially in industrial visual inspection or related settings, and you enjoy careful, methodical quality work. This role suits contractors seeking steady part-time hours and contributors who want to build expertise in annotation QA.

• Intermediate-level annotators and QA reviewers
• People with experience in industrial or machine-vision annotation projects
• Contributors seeking 100% remote, contract work

Compensation, schedule, and next steps

This is a part-time contractor role paid as a fixed-price contract of USD 1,200. The project expects 20+ hours per week of effort. OpenTrain AI hires and contracts contributors directly; after applying, you'll receive project guidelines, access to the CVAT workspace, and sample frames to begin work.

• Employment type: Contractor, Part-time
• Pay: Fixed price USD 1,200 (total contract amount)
• Time commitment: 20+ hours per week
• Worldwide applicants welcome; fluent English required