Toast POS Hospitality Workflow Reviewer

The Work

You will help improve AI systems' understanding of restaurant technology and point-of-sale operations. The work combines practical hospitality knowledge with clear written and verbal explanations of how restaurant systems are configured, used, and improved.

  • Analyze Toast POS workflows for order entry, payment processing, reporting, and restaurant operations.
  • Create realistic, scenario-based documentation and step-by-step guides based on restaurant procedures.
  • Review Toast POS functionality and explain usability, implementation, and troubleshooting challenges.
  • Describe configuration and optimization practices for quick-service, casual, and fine-dining restaurants.
  • Annotate and evaluate transaction data, menus, and order flows for AI training.
  • Collaborate on prompts, tasks, and datasets and explain Toast POS concepts to technical and non-technical audiences.

What It Pays and Takes

This is a part-time contractor role for people with current, hands-on experience using Toast POS in hospitality work.

  • $28 to $92 per hour.
  • Part-time contractor work.
  • Open to candidates in the listed countries across the Americas, Europe, Asia, Africa, and the Middle East.
  • Fluent in English.
  • Current hospitality employment with daily hands-on use of Toast POS is required.
  • Strong understanding of restaurant ordering, payment, and point-of-sale workflows.
  • Excellent written and verbal communication.
  • Able to document processes for both technical and non-technical audiences.
  • Understanding of how POS needs differ across quick-service, casual, and fine-dining restaurants.
  • Experience training, mentoring, or supporting people who are adopting restaurant technology is helpful.

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 learn from examples, explanations, and evaluations. People with practical experience are needed to show AI how real-world processes work and to judge whether its results are useful and accurate.

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