LLM Content Evaluator (Chinese)

You will review written content and analytical scenarios to help large language models produce more accurate, well-supported answers. The work combines Chinese and English comprehension, online research, logical reasoning, and detailed written feedback.

• Read and summarize substantial written content by breaking it into logical sections.
• Research information online and validate claims in source material.
• Answer questions involving trends, data interpretation, logical rules, and basic arithmetic.
• Create scenarios and responses that help models improve their reasoning and analytical performance.
• Provide correct answers, explanations, constructive feedback, and detailed annotations.
• Use creative and lateral thinking to work through unfamiliar problems.

The listing does not state a pay rate. This is a remote contractor assignment with a full-time weekly commitment, and the structured requirement is 20 or more hours per week.

• Work arrangement: Remote contractor assignment.
• Time requirement: 20 or more hours per week.
• Schedule: Flexible hours are possible within the required overlap with US Pacific time.
• Location: Worldwide.
• Languages: Strong written and reading ability in English and Chinese.
• Experience level: Entry level.
• Equipment: A desktop or laptop with a reliable internet connection.
• Required skills: Analytical and critical thinking, research, communication, data interpretation, logical reasoning, and clear written explanations.
• Helpful background: Business analysis, research, journalism, copywriting, technical writing, editing, translation, engineering, literature, communications, arts, or statistics.
• Helpful tools and knowledge: Excel, Google Suite, data interpretation, logical reasoning, and basic arithmetic.
• Work style: Self-motivated and able to work independently in a remote setting.

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

AI training work is the human side of building artificial intelligence. People review content, check model answers, and provide examples and feedback so language models can improve; strong research, reasoning, and language skills are valuable for this work.