The work
You will complete assigned activities using Google Wallet and Plaid, then provide clear feedback about account setup and the task experience. You will also report issues, follow secure project instructions, and protect project information.
The project details describe Google Wallet and Plaid task evaluation, while the role title identifies personal account generalist raters. Review the duties and qualifications before applying.
- Complete assigned Google Wallet and Plaid activities.
- Give accurate feedback about account setup and task experiences.
- Report problems found during the assigned activities.
- Follow the required secure process and maintain confidentiality.
- Complete consent and confidentiality documents.
What it pays and takes
This is an entry-level, remote contractor engagement for people based in South Korea. The work may continue for up to 16 weeks and requires regular participation during Pacific Time overlap.
- Pay: No pay details are provided.
- Schedule: At least 4 hours per day and 20 hours per week.
- Time overlap: At least 4 hours overlapping with Pacific Time.
- Location: Open to candidates currently based in South Korea.
- Language: Fluent in Korean.
- Google Wallet: Actively use the service, with at least one linked payment method such as a credit card, debit card, or bank account.
- Saved passes: Have at least five saved passes, such as loyalty cards, transit passes, event tickets, or membership cards.
- Plaid: Have an existing Plaid account or be willing to securely connect a bank account through Plaid.
- Other requirements: Follow instructions carefully, provide accurate feedback, use the relevant services for project tasks, and protect confidential information.
- Security: Project activities do not require passwords, PINs, CVV numbers, or other confidential login details.
How it works
Apply on OpenTrain with your resume and then complete the application on the hiring site.
About AI training work
AI training work is the human side of building artificial intelligence. People complete tasks, review results, and provide feedback so AI systems can learn from reliable examples, with experienced contributors often taking on more specialized work.