Career and Technical Education Professors for AI Evaluation

You will help improve AI models that work with career and technical education concepts, workplace tasks, and field-specific language. The work uses your experience in teaching, student assessment, curriculum development, and vocational instruction.

No prior AI experience is required. You will learn to create prompts and evaluate model responses using the standards and context of your field.

• Write prompts based on real career and technical education work, instruction, and workplace language.
• Review AI-generated responses and content related to your professional field.
• Give clear, structured feedback to improve the accuracy and usefulness of model outputs.
• Assess written content and explain your decisions clearly and constructively.
• Review model outputs against career and technical education standards and context.

What it pays and takes

This is remote, asynchronous project work that you complete independently. Projects operate year-round and open periodically across different areas of expertise.

• Pay: Up to $75 per hour.
• Time: 20 or more hours per week.
• Location: Open to candidates in the United States.
• Language: Professional fluency in English.
• Experience: At least four years in college vocational instruction, career and technical education, or closely related teaching work.
• Experience evaluating and guiding student progress through feedback and testing.
• Experience developing and delivering lectures, discussions, curricula, or practical training.
• Familiarity with academic and vocational pathways, student advising, or workplace-focused education.
• Eligible F-1 students may be able to participate through CPT or OPT, subject to school and work authorization requirements.

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 understand information. Contributors create examples, review model responses, and provide feedback so AI produces more accurate and useful results; people with relevant professional experience are paid for the judgment their expertise brings.