Creative Technologist (Audio, Design, UX)

You will help evaluate AI systems across audio, design, and user experience. The work focuses on expert judgment and clear standards, not production engineering.

The duties and qualifications focus on AI evaluation across audio, design, and UX. Review them before applying to make sure the role matches your background.

• Design realistic technical scenarios and problem sets in your area of creative technology expertise.
• Write expert reference answers that show strong professional judgment.
• Create grading rubrics that separate correct, excellent, and deficient responses.
• Evaluate AI-generated outputs for correctness, depth, and practical domain judgment.
• Write clear technical explanations and structured feedback about evaluation standards.

This is a remote, part-time contract role.

• Pay: $135 per hour.
• Time requirement: 20+ hours per week.
• Work arrangement: Remote, independent, and asynchronous.
• Location: Open to candidates in listed countries, including the United States, Canada, Australia, India, Singapore, and the United Kingdom.
• Language: Fluent English.
• Experience: Six to ten years in creative technology, media, audio, design, UX, or a closely related area.
• Professional background: Current or recent hands-on work, rather than a purely academic background.
• Education: Bachelor's degree required; master's degree welcomed.
• Communication: Strong writing skills for technical explanations, reference answers, rubrics, and structured feedback.
• Helpful experience: Reviewing or grading technical work, peer review, code review, grading, or editing.
• Additional signals: Research publications, open-source contributions, recognized work products, audio engineering, linguistics, or multimodal design experience.

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

AI training work uses human-created examples, reviews, and feedback to help artificial intelligence produce better results. People with strong professional judgment are paid to define quality, assess model outputs, and explain what good work looks like.