You will help evaluate and improve AI content related to psychology. The work uses case studies, assessments, and model-generated responses, with clear written feedback to help AI systems learn from expert judgment.
- Write or improve expert responses and explain your reasoning clearly.
- Review source materials and AI-generated outputs against project guidelines.
- Explain your decisions so feedback can improve model behavior.
- Apply the same quality standards and review process across repeated tasks.
What it pays and takes
This is remote contractor work with flexible weekly hours over 1 to 3 months. The role is suited to someone with strong psychology knowledge, careful written communication, and the ability to work independently.
- Pay: $100 to $200 per hour.
- Estimated project earnings: $16,000 to $32,000 based on an OpenTrain assumption of 20 hours per week over 1 to 3 months.
- Languages: professional fluency in Russian and English.
- Education: PhD in psychology or a closely relevant area, as stated in the role title.
- Relevant professional, academic, or language expertise in psychology AI content evaluation.
- Strong written communication and close attention to detail.
- Ability to follow detailed instructions and apply review rubrics consistently.
- Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, Ethiopia, France, the United Kingdom, Ghana, and Greece.
- Open to candidates in Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, and Qatar.
- Open to candidates in Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that write, answer questions, and make decisions. Reviewers assess examples and explain what is accurate, useful, and well-supported so models can improve; specialized knowledge is especially valuable for subject-specific projects.