Remote Bilingual Japanese Psychologist (PhD) for AI Data

micro1; United States; Remote; USD 110,000 - 165,000; Part time

Job summary

micro1 is seeking a Bilingual Japanese Psychologist (PhD) for a remote contract role contributing expertise to AI data training projects. You will analyze psychological case studies, create bilingual Japanese-English materials, and evaluate content for ethical alignment.

The position emphasizes cultural sensitivity, clear documentation, and collaboration with interdisciplinary teams to ensure accurate, responsible model training across languages and contexts.

Qualifications

• PhD in Psychology from clinical or academic setting.
• Native or near-native fluency in Japanese and English.
• Strong analytical and ethical decision-making skills.
• Experience developing or evaluating case studies.
• Excellent written and spoken communication for bilingual concepts.

Responsibilities

• Analyze and assess psychological case studies and documentation, providing feedback based on professional experience.
• Develop culturally sensitive psychological scenarios and materials in both Japanese and English for data enrichment and model training.
• Evaluate AI-generated content for accuracy, ethics, and alignment with psychological best practices.
• Collaborate with interdisciplinary teams to share perspectives and ensure holistic solutions.
• Document evaluation processes and findings clearly to support transparency and reproducibility.
• Apply bilingual communication to interpret and refine psychological assessments across languages.

Skills

Bilingual Japanese-English

Analytical thinking

Ethical decision-making

Cross-language translation

Remote collaboration tools

Education

PhD in Psychology

Job description

micro1 is seeking a Bilingual Japanese Psychologist (PhD) for a remote contract role contributing expertise to AI data training projects. You will analyze psychological case studies, create bilingual Japanese-English materials, and evaluate content for ethical alignment.

The position emphasizes cultural sensitivity, clear documentation, and collaboration with interdisciplinary teams to ensure accurate, responsible model training across languages and contexts.