Customer Service Conversation AI Training Expert

You will create realistic customer support conversations for speech-to-speech AI agents. You will act out scenarios using professional communication and established service workflows.

You will also review and rank AI responses, test models for inaccuracies or bias, and assess their reliability across different customer service situations. Follow the project scenarios, instructions, and quality standards provided for each task.

• Create natural, human-enacted conversations across realistic customer support scenarios.
• Use customer service judgment in issue identification, troubleshooting, escalation, follow-up, and resolution.
• Evaluate AI responses for accuracy, fluency, and contextual relevance.
• Test AI models for inaccuracies, bias, and reliability across different use cases.
• Demonstrate active listening, empathy, problem-solving, and professional communication.

This is remote contractor work open to candidates in Canada. It is part-time work requiring at least 20 hours per week.

• Pay: Up to $30 per hour in US dollars.
• Location: Remote; open to candidates in Canada.
• Time: 20+ hours per week.
• Experience: At least two years of professional customer service or call center experience.
• AI experience: At least one year in data annotation, AI evaluation, model training, response evaluation, or related AI training work.
• Education: A bachelor's degree or higher in Business Administration, Communications, Marketing, Management, or a related field, or equivalent professional experience.
• Skills: Strong knowledge of end-to-end customer support and experience handling inquiries, complaints, service requests, and escalations.
• Communication: Fluent spoken English and the ability to adjust your communication style and tone to customer needs.
• Work style: Reliability and self-direction in remote contractor work.

Apply on OpenTrain with your resume and then complete the application on the hiring site.

AI training is the human work behind systems that learn from examples, including recorded conversations and reviewed AI responses. People with practical customer service experience help these systems communicate more accurately, naturally, and appropriately.