Psychologist for AI Evaluation (Japanese)

You will use psychology expertise to review and improve material used to train and evaluate AI systems. The work covers case studies, psychological documentation, assessments, and AI-generated content in Japanese and English.

• Review psychological case studies and documentation, then provide feedback based on professional experience.
• Create culturally sensitive psychological scenarios and materials in Japanese and English.
• Evaluate AI-generated content for accuracy, ethical soundness, cultural sensitivity, and alignment with psychological best practices.
• Interpret and refine psychological assessments across languages and cultural settings.
• Record evaluation methods and findings clearly so the work can be understood and repeated.
• Work with contributors from different fields to address varied user needs.

What it pays and takes

This is a part-time contractor role for a psychologist with advanced academic and professional experience. Prior AI or technology experience is not required.

• Pay: $100 to $200 per hour.
• Education: PhD in Psychology.
• Professional background: Demonstrated experience in clinical and academic settings.
• Languages: Professional fluency in Japanese and English, including complex psychological terminology.
• Required skills: Psychological case study or assessment development and evaluation, strong analysis and critical thinking, ethical decision-making, bilingual communication, cultural sensitivity, and familiarity with digital tools for remote collaboration and documentation.
• Helpful background: Active clinical practice and relevant psychology publications.
• Location: Open to candidates in the countries specified for this role, including Japan, the United States, Canada, the United Kingdom, and countries across Europe, Asia, Africa, and the Americas.

How it works

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

About AI training work

AI training is the human work behind systems that generate and understand text. People review examples, write or assess content, and provide expert feedback so models produce more accurate, useful, and responsible results.