About OpenTrain OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. The platform connects people to real projects where they teach AI by annotating data, reviewing model outputs, and shaping how modern systems behave. Work through OpenTrain to start building experience in a fast-growing field: flexible, remote opportunities that are accessible without prior specialist experience and let you contribute directly to cutting-edge AI. About AI training work AI training (data labeling / annotation) is the human work behind machine learning: people prepare and review examples that models learn from. Many projects are part-time and remote, making this work a flexible way to earn while developing practical skills.

• Flexible, remote work you can fit around other commitments.
• Entry-level projects are common; attention to detail and consistency matter most.
• Contributors help shape how AI systems interpret visual scenes and sports actions.

The role You will label volleyball actions in images by drawing bounding boxes and tagging the action type. Action categories: Spike, Block, Serve, Set, Receive. This is an entry-level, part-time contractor role for contributors worldwide. Work is less than 20 hours per week and performed using the CVAT labeling tool.

• Project type: Image annotation with bounding boxes.
• Labeling software: CVAT.
• Employment type: Contractor, Part-time.
• Availability: Less than 20 hours per week, worldwide applicants welcome.

What you'll do Follow the project guidelines and examples to locate players and draw accurate bounding boxes around the person or body parts involved in the action, then assign the correct action label. Work consistently to meet quality expectations; labeled images will be reviewed and feedback provided to help you improve.

• Draw bounding boxes around players performing each action.
• Tag each box with one of: Spike, Block, Serve, Set, Receive.
• Follow provided examples and annotation guidelines; examples will be added to the project.
• Submit annotated images through CVAT for review.

Requirements

This is an entry-level role and no prior annotation experience is required, but you should have good visual attention to detail and the ability to follow written instructions. You must have a reliable internet connection and a computer capable of running CVAT in a web browser. Candidates worldwide may apply.

• Experience level: Entry level — willingness to learn and follow guidelines is essential.
• Technical: Internet access and a computer with a modern browser to run CVAT.
• Availability: Up to 20 hours per week (part-time).
• Language: No specific language requirements listed.

Compensation and schedule Payment is per label at a rate of $0.03 USD per label. This project uses a pay-per-label model rather than an hourly wage. You will work as a contractor and set your own schedule within the project's part-time limits. Expect to receive examples and guideline updates as the project progresses.

• Pay structure: Pay-per-label ($0.03 USD per label).
• Work type: Contractor, part-time, remote.
• Hours: Less than 20 hours/week; flexible scheduling.

How it works Apply through the OpenTrain project listing to join this annotation task. Once accepted you will receive access to the dataset, the CVAT workspace, and the annotation guidelines and examples. Complete tasks in CVAT, submit labeled images, and incorporate feedback from reviewers to improve quality. The project owner will add example annotations to help you get started.

• Onboarding includes access to project guidelines and example annotations.
• Label in CVAT and submit work for review; feedback helps you improve accuracy.
• Worldwide contributors are welcome to apply and work remotely.