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Japanese Image Caption Review Specialist

OpenTrain AI

AI Training & Data Labeling

100% Remote Hourly · $30/hr

$30/hr

Compensation

Worldwide

Eligibility

Entry

Experience

Sep 5, 2026

Posted

Open worldwide

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About OpenTrain
OpenTrain is the centralized, open platform where AI training and data-labeling freelancers find work, consolidate opportunities across platforms, and build a unified AI training portfolio they control. We make specialized AI training work easier to track, apply for, and grow into a durable freelance career.

About this role
OpenTrain is recruiting for a Japanese Image Caption Review Specialist to support AI training work focused on Japanese image caption review. You will compare captions produced by an AI model with text shown inside images, including signage, labels, packaging, and screenshots. You will identify text that is misread, mistranslated, or omitted and document each issue with the exact wording visible in the image. This is a remote contractor role paying $30 per hour.

What you will do
Review image content and model-generated captions against project guidelines. Compare Japanese text character by character and record clear, evidence-based findings in English. Explain caption defects precisely so feedback can improve model behavior. Maintain accuracy and consistency across repeated review tasks.

Required skills
Native-level Japanese ability and fluent English writing skills are required. You should have a bachelor's degree, at least two years of professional experience, and strong attention to detail when reviewing visual text. The role also requires careful judgment, patience with repetitive comparison work, and the ability to follow detailed instructions independently in a remote contractor setting.

Why work with OpenTrain
OpenTrain gives freelancers one place to manage AI training opportunities instead of rebuilding proof of work on every platform. A stronger OpenTrain profile helps you show credible experience, discover roles that match your skills, and turn AI training and data-labeling work into a long-term portfolio.

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