You will create and review complex psychiatric content used to train and evaluate AI systems in mental health settings. The work requires clinical judgment, bilingual documentation, cultural awareness, and careful review of evaluation methods.
- Develop complex psychiatric case studies for AI model training.
- Conduct psychological assessments and create expert annotations reflecting Cantonese-language psychiatric practice.
- Write clinical documentation and analytical reviews in Cantonese and English.
- Review AI evaluation methods used in mental health contexts and provide expert feedback.
- Build bilingual communication frameworks for accurate psychiatric information exchange.
- Apply ethical reasoning, cultural sensitivity, and confidentiality when reviewing sensitive case content.
- Collaborate with technology, research, or digital health teams.
What it pays and takes
This is a remote, part-time contractor opportunity. The project schedule and duration will be confirmed for the engagement.
- Pay: $100 to $200 per hour.
- Time requirement: 20 or more hours per week.
- Languages: Fluent Cantonese and advanced written and spoken English.
- Location: Remote, with eligibility based on the countries listed for this role.
- Required education: MD, MBBS, or equivalent medical degree.
- Required training: Completed psychiatry residency and a valid medical license.
- Required experience: Psychiatric assessment, treatment planning, and case documentation in Cantonese-speaking clinical settings.
- Knowledge: Familiarity with Western psychiatric frameworks and their use with Cantonese-speaking patients.
- Professional strengths: Strong ethical judgment and cultural sensitivity in complex mental health situations.
- Helpful background: Creating teaching materials or case studies for education or research, and working on technology, research, or digital health projects.
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 learn from examples, including written case studies, expert ratings, and detailed reviews. People with specialized experience are paid to help models handle complex subjects accurately and responsibly.