Quality Assurance Analyst

Thoth AI; Philippines; Remote; PHP 240,000 - 420,000; Full time

Job summary

Thoth AI is seeking a detail-oriented Quality Assurance Analyst to join our remote team in the Philippines. You will review annotation outputs, perform quality audits, and provide actionable feedback to improve accuracy and consistency across AI labeling projects.

You will monitor quality metrics, identify trends, and collaborate with Project Managers and annotators to drive continuous data quality improvements while upholding documented guidelines and processes.

Qualifications

• Strong attention to detail and analytical thinking required.
• Excellent written and verbal English communication.
• Ability to interpret and apply complex guidelines consistently.
• Strong organizational and reporting skills.
• Proficiency with spreadsheets, reporting tools, and web-based platforms.
• Ability to work independently in a remote environment and meet deadlines.

Responsibilities

• Review and audit annotation outputs across various project types to ensure compliance with project guidelines and quality standards.
• Conduct quality evaluations of text, image, video, audio, and other annotation tasks as required.
• Identify labeling errors, inconsistencies, and process gaps, providing clear and constructive feedback.
• Monitor quality metrics and maintain audit reports to track performance and improvement opportunities.
• Perform Root Cause Analysis (RCA) on quality issues and recommend corrective actions.
• Participate in calibration sessions to ensure consistent interpretation of annotation guidelines.
• Support the development and delivery of quality-related training and guideline updates.
• Collaborate with Project Managers, Operations teams, and annotators to improve overall data quality.
• Escalate recurring quality concerns and contribute to continuous process improvement initiatives.

Skills

Attention to detail

Analytical thinking

English proficiency

Guidelines interpretation

Organizational skills

Reporting skills

Spreadsheet tools

Remote work

Tools

Spreadsheet software

Web platforms

Reporting tools

Job description

We are seeking a detail-oriented and analytical Quality Assurance Analyst to join our growing team. In this role, you will review annotation outputs, conduct quality audits, identify quality trends, and provide actionable feedback to ensure annotation accuracy and consistency across projects. You will play a key role in maintaining high-quality datasets that support AI model

development.

Key Responsibilities

• Review and audit annotation outputs across various project types to ensure compliance with project guidelines and quality standards.
• Conduct quality evaluations of text, image, video, audio, and other annotation tasks as required.
• Identify labeling errors, inconsistencies, and process gaps, providing clear and constructive feedback.
• Monitor quality metrics and maintain audit reports to track performance and improvement opportunities.
• Perform Root Cause Analysis (RCA) on quality issues and recommend corrective actions.
• Participate in calibration sessions to ensure consistent interpretation of annotation guidelines.
• Support the development and delivery of quality-related training and guideline updates.
• Collaborate with Project Managers, Operations teams, and annotators to improve overall data quality.
• Escalate recurring quality concerns and contribute to continuous process improvement initiatives.

Requirements

• Strong attention to detail and analytical thinking skills.
• Excellent written and verbal communication skills in English.
• Ability to interpret and apply complex guidelines consistently.
• Strong organizational and reporting skills.
• Proficiency with spreadsheets, reporting tools, and web-based platforms.
• Ability to work independently in a remote environment and meet deadlines.

Preferred Qualifications

• Previous experience in Quality Assurance, Data Annotation, Content Moderation, AI Training, or similar operational roles.
• Experience conducting audits, quality reviews, or calibration exercises.
• Familiarity with AI data labeling workflows and quality management processes.
• Experience with Root Cause Analysis (RCA) and performance reporting.