Japanese-Speaking AI Language Model Analyst

As a Japanese AI Language Model Analyst, you will review written content, analytical questions, and logic scenarios. Your work will help AI systems learn from accurate answers, structured reasoning, and clear human feedback.

You will work with text tasks such as question answering, summarization, and text generation. You will also check model outputs against project guidelines and keep your judgments consistent across repeated evaluations.

• Analyze and summarize substantial written content into logical sections.
• Research information online, check claims, and explain conclusions clearly.
• Answer analytical questions and create reasoning scenarios.
• Solve logic, data interpretation, and basic arithmetic problems.
• Write accurate answers, detailed explanations, constructive feedback, and annotations.
• Review materials and model outputs against detailed guidelines.

What it pays and takes

This is a part-time contractor role for candidates who can work independently in a remote setting. The role is open worldwide, with work conducted in Japanese and English.

• Pay: The listing does not specify a rate.
• Time: 20 or more hours per week.
• Location: Worldwide and remote.
• Languages: Strong written English and working ability in Japanese.
• Experience: Entry level; prior AI training experience is not required.
• Skills: Research, analytical reasoning, creative and lateral thinking, data interpretation, logic, basic arithmetic, and clear written communication.
• Helpful background: Business analysis, research, journalism, editing, translation, or technical writing.
• Useful tools: Excel and Google Suite.
• Work style: Self-motivated, independent, and able to follow detailed instructions and quality standards.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind systems that answer questions, summarize text, and generate language. People review examples and model outputs, explain what is correct or useful, and provide feedback that helps improve how these systems respond.