Machine Learning Data Associate

About the Role

Machine Learning Data Associates are annotation specialists who support machine learning projects through high-quality data annotation, labeling, and analysis. In this role, you will help improve customer experience and the performance of ML models by producing accurate, reliable data that trains and evaluates these systems. You will work under the guidance of an operations team of subject matter experts, contributing to a wide range of projects that directly shape how customers interact with automated support. 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 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.

Requirements & Tech Stack

• English: Speak, write, and read fluently.
• Education: Bachelor's degree or equivalent.
• Skills:
• Strong analytical skills.
• Attention to detail.
• Effective communication abilities.
• Ability to work proactively and independently.
• Ability to meet deadlines and deliver on projects and tasks.

Preferred Qualifications

• Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup.
• Experience working with speech and text language data in multiple languages.
• Experience using customer insights and data to deeply understand target customers and dive deep.
• Experience prioritizing and handling multiple assignments at any given time while maintaining commitment to deadlines, or experience completing complex tasks quickly with little to no guidance and react with appropriate urgency to situations that require a quick turnaround.
• Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience in computer architecture.
• Familiarity with evaluating conversational or automated customer service experiences.