DESCRIPTION:
This role is ideal for detail-oriented individuals who enjoy structured, guideline-driven work and want to play a direct part in advancing conversational AI and customer service technology.
Key job responsibilities
Data Annotation and Labeling
- Perform accurate annotation and labeling tasks that support model training and fine-tuning.
- Complete intent and dialogue labeling for language understanding and intent detection systems.
- Conduct multi-turn free-text annotation to support conversational AI experiences.
- Author simulated conversations used for testing and training.
Quality Assurance and Testing
- Test customer service models based on specific prompts to confirm intent detection and routing work as intended.
- Read and analyze customer contacts to identify defects and improvement opportunities.
- Audit question-and-answer pairs across multiple marketplaces for policy compliance and accuracy.
- Compare call audio to written transcripts to evaluate and improve transcription accuracy.
Analysis and Evaluation
- Complete customer experience analysis by reading contacts and assessing customer sentiment.
- Identify opportunities for improvement through structured contact review.
- Flag compliance issues, including exposure of personally identifiable information and policy violations.
- Review the quality of response templates used by automated customer service agents.
Performance and Development
- Maintain high quality standards across all assigned projects.
- Track and meet throughput targets and key performance indicators.
- Collaborate with project leads and the wider operations team.
- Participate in upskilling initiatives to build expertise across a variety of project types.
A day in the life
You start your day by reviewing your assigned projects and the guidelines for each. You might start with labeling customer conversations to help train a model to better understand what customers are asking for, then move into auditing question-and-an