Personalization AI Response Evaluator (Dutch)

You will evaluate how well an AI system uses personal context in multi-turn conversations. You will create prompts based on your own experiences, review responses, compare alternatives, and explain your judgments clearly.

Your feedback will focus on whether personalization is helpful, natural, accurate, and supported by available information. You will also review debugging details to check whether conversation summaries and relevant data sources were used correctly.

• Create and run multi-turn prompts that require the AI to use relevant personal context.
• Find unsupported claims, hallucinations, incorrect personalization, weak inferences, forced connections, and unnatural overnarration.
• Compare responses side by side and rank them for helpfulness, ease of use, and overall quality.
• Write clear rationales that refer to specific conversation turns and explain strengths and problems.
• Provide detailed annotations and constructive feedback.

This is a remote contractor engagement for one month. The project supports a global operations team, but specific country eligibility is not stated.

• Pay: $20 per hour.
• Schedule: At least 4 hours per day, up to 40 hours per week.
• Structured commitment: 20 or more hours per week.
• Time zone: 4 hours of overlap with Pacific Time.
• Language: Strong Dutch reading and writing ability is essential.
• Level: Entry level, with strong analytical judgment required.
• Education: A bachelor's degree or equivalent experience in policy, law, ethics, linguistics, journalism, computer science, or a related analytical field is requested.
• Helpful experience: Data annotation, AI quality evaluation, content moderation, or related work.
• Equipment: A desktop or laptop and reliable internet connection.
• Work style: You should be able to work independently and evaluate nuanced or ambiguous AI responses.

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

AI training work is the human work behind systems that learn from examples, including reviewing and rating model responses. People with careful judgment are paid to identify errors, compare quality, and help make AI behavior more useful and reliable.