Image Classification for Human-Feedback Example Generation

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect people with remote annotation projects that directly shape state-of-the-art AI systems. This role is hired and managed by OpenTrain as part of our growing set of training assignments.

About AI training work

AI training (also called data labeling or human-feedback work) is the human side of building intelligent systems: people create, review, and rate examples that teach models how to behave. These projects are often remote, flexible, and accessible to entry-level contributors while offering the chance to work on cutting-edge AI development.

This project focuses on producing labeled image examples used in human-feedback pipelines that improve large language models' behavior when LLMs must reason about or describe visual information.

Project overview

You will classify images using CVAT to produce high-quality labeled examples that feed into a human-feedback training workflow for LLMs. The work is classification-focused: selecting the correct category or label for each image according to provided guidelines and examples.

This is a contract, part-time engagement requiring 20+ hours per week. The project accepts contributors worldwide and is open to entry-level applicants who meet the stated requirements.

• Data type: images (classification tasks)
• Labeling tool: CVAT
• Time commitment: 20+ hours per week
• Employment: Contractor, Part-time
• Worldwide applicants accepted

What you'll do

Follow detailed annotation guidelines to assign the correct class labels to images in CVAT. Work consistently to meet accuracy and throughput targets set for the project.

• Open image tasks in CVAT and apply the correct classification label per guideline examples.
• Review your labeled work for consistency and quality before submission.
• Flag ambiguous or problematic images for reviewer QA when instructed.
• Complete batches of labels on a schedule to meet weekly throughput expectations.

Requirements

We welcome entry-level contributors but require the specific items below. All requirements come from the project brief and are enforced to ensure data quality.

• Education: Graduate from university (required).
• Experience: Entry level — previous professional annotation experience is not required.
• Availability: Able to commit 20+ hours per week for the duration of the contract.
• Tools: Comfortable using CVAT or willing to learn the platform quickly.
• Location: Open to candidates worldwide.

Compensation, contract, and next steps

This project is a fixed-price contract with total compensation of USD 127,500 for the contracted scope (payment terms will be provided in the contract). You will be engaged as a contractor and expected to manage your schedule within the 20+ hours/week requirement.

To apply, create an OpenTrain account (free), complete your profile, and submit any requested verification or sample tasks. Qualified applicants will receive onboarding instructions, project guidelines, and CVAT access.

• Payment type: Fixed-price (USD 127,500 total, per project brief).
• Hiring model: Contractor, part-time.
• How to apply: Sign up on OpenTrain, complete your profile, and submit the application for this role.