BA Generalist (English Creative Data Annotation)

You will help evaluate how well a language model handles personal, professional, and interpersonal situations. You will create realistic, ongoing scenarios, interact with the model under assigned conditions, and assess the responses.

Your written explanations will show why a response is or is not relevant, useful, personalized, clear, and aligned with the situation. You will follow project guidelines and complete assigned tasks within the required timeline.

• Create realistic social scenarios involving personal, professional, or interpersonal situations.
• Interact with a language model under assigned evaluation conditions.
• Rate responses for relevance, usefulness, personalization, clarity, and contextual alignment.
• Write clear, detailed reasons for your ratings.
• Apply project guidelines to each assigned task.

Compensation is paid per completed label. The engagement is remote, short term, and expected to run for about 2 to 3 weeks, with an expected start around October 1 or a nearby date.

• Pay: Per completed label; no per-label amount is provided.
• Time: Full-time engagement with at least 20 hours per week.
• Location: Remote and open worldwide.
• Language: Strong written English and clear communication skills.
• Experience level: Entry level.
• Core skills: Creative and analytical thinking, realistic scenario development, understanding of nuanced interpersonal situations, and objective evaluation of AI-generated responses.
• Relevant backgrounds: Business analysis, English, literature, journalism, creative writing, scriptwriting, content writing, film and video captioning, human-AI interaction, or a related field.
• Helpful experience: Three or more years in data annotation, human-AI interaction, content evaluation, or comparable analytical work, plus copywriting, data analysis, or critical thinking experience.

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

AI training is the human work behind artificial intelligence. People create examples and review model responses so AI systems can become more useful, clear, and reliable; experienced contributors are often valued for their subject knowledge and careful judgment. OpenTrain helps people find these projects, build a profile, and apply in one place.