AI Safety Data Annotation Specialist

You will evaluate AI-generated conversations and model outputs using AI safety policy rubrics. Your reviews will help AI systems learn from consistent human judgments and clear written feedback.

• Review source materials and model outputs against project guidelines.
• Apply safety policies and structured rating rubrics to each review.
• Record evidence-based judgments about model behavior.
• Explain your decisions clearly and objectively.
• Maintain accuracy and consistency across repeated review tasks.
• Review sensitive content involving self-harm, violence, and abuse.

Compensation details are not specified in the listing. The role is structured as remote, part-time contractor work with flexible scheduling.

• Schedule: About 20 hours per week for an estimated 1 to 3 months.
• Location: Remote and open worldwide.
• Language: Fluent in English.
• Experience level: Entry level; prior AI training experience is not required.
• Strong reading comprehension and close-reading skills.
• Ability to write clear, concise, and objective evaluations.
• Excellent attention to detail and awareness of subtle nuances.
• Strong judgment and ability to follow detailed safety policies.
• Ability to work accurately under time constraints.
• Familiarity with United States references, systems, and terminology.
• Helpful background includes data annotation, content moderation, policy review, trust and safety, AI training, response evaluation, editorial review, proofreading, compliance, or quality assurance.

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

AI training is the human work behind systems that learn from examples, including reviewing model responses and rating their quality and safety. People with strong subject knowledge are valued because careful, consistent judgments help improve how AI systems behave.