Hospitality Professional for AI Model Training

Hospitality professionals apply front-desk and guest service expertise to develop and evaluate domain-specific prompts and to review large language model responses, improving AI understanding of hotel, motel, and resort operations.

• Develop domain-specific prompts and tasks for large language models.
• Evaluate and score LLM responses for accuracy, usefulness, and domain relevance.
• Conduct independent research on hospitality topics, using AI tools as an aid.
• Contribute subject-matter expertise to improve AI performance across hospitality subdomains.
• Participate asynchronously in projects, with placement dependent on project availability.

• Undergraduate students currently studying hospitality are invited to participate.
• Minimum 4 years of work experience in hotel, motel, or resort front-desk roles is required.
• Comfortable working primarily asynchronously and collaborating with researchers or AI teams.
• Confidence that your domain expertise can exceed current AI systems in explaining key hospitality concepts.
• Interest in learning new skills while contributing to applied AI research across disciplines.

• Employment type: Part time.
• Remote, asynchronous work from any location.
• Flexible schedule, there is no minimum required number of hours.
• The program runs year-round, however project availability varies by domain and placement depends on open projects.

Up to $60/hr (depending on the project)

• F-1 students who qualify for CPT or OPT may be eligible to participate. Confirm eligibility with your Designated School Official.
• If your school requires enrollment in a CPT course for authorization, this program may not meet that requirement.
• STEM OPT is not supported for this program.

• Create an account and complete the required profile information.
• Complete identity verification as part of eligibility checks.
• Apply to or join relevant projects and complete any project-specific onboarding steps.
• Begin assigned work and receive compensation according to the project terms.