LLM Analyst (Dutch)

You will review written content and model training examples to help improve large language models. Your work will involve answering questions, checking whether claims are supported, explaining your reasoning, and giving clear feedback.

Some tasks may involve interpreting sales data over time, solving rule-based puzzles, and deciding whether an answer follows logically from the available information.

• Read, summarize, and divide long content into clear logical sections.
• Research information online and validate claims in written content.
• Answer analytical, logical, quantitative, and reasoning-based questions.
• Create scenarios and examples that help language models learn from mistakes.
• Provide accurate answers, explanations, constructive feedback, and detailed annotations.
• Use creative and lateral thinking when solving unfamiliar problems.

This is a remote, part-time contractor assignment. The project may be extended based on your performance and project needs.

• Pay: The listing does not provide a rate.
• Time: At least 20 hours per week.
• Location: Remote and open worldwide.
• Languages: Fluent written English and Dutch.
• Experience: Entry level applicants are welcome.
• Skills: Strong analysis, research, English comprehension, basic arithmetic, and logical reasoning.
• Communication: Explain conclusions clearly and give specific, useful feedback.
• Work style: Work independently and communicate well in writing.
• Helpful background: Business analysis, research, journalism, copywriting, technical writing, editing, or translation.
• Education: A bachelor's degree or current undergraduate study in engineering, literature, journalism, communications, arts, statistics, or a related field is welcome. Relevant experience may also be considered.
• Tools: Familiarity with Excel and Google Suite is useful.

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

AI training is the human work behind systems that understand and generate language. Analysts review examples, check answers, and explain reasoning so models can become more accurate and useful.