AI Data Quality Architect

23 hours ago

Taguig, National Capital Region, Philippines beBeeData Full time $100,000 - $150,000
Overview

About the Role: TaskUs seeks a proactive leader to architect and uphold high-quality annotation workflows so AI models are built and evaluated on reliable data without compromising on speed or efficiency.

The Impact You'll Make:

  • Build and guide a high-performing team: Lead and mentor a team of Data Quality Analysts, setting clear quality goals, delivering feedback, and fostering a culture of precision and accountability.
  • Ensure quality at scale: Develop and continually refine robust QA processes, SOPs, and statistical quality metrics (e.g., F1 score, inter-annotator agreement) to protect the integrity of annotation outputs.
  • Drive transparency and insight: Create dashboards and reports that reveal quality trends, root causes of errors, and improvement opportunities - communicating these insights to leadership and clients.
  • Champion tool innovation and efficiency: Manage annotation and QA platforms, and lead the evaluation or implementation of new automation tools to elevate efficiency and maintain quality.

Key Responsibilities

Strategic Leadership

  • Drive the development, refinement, and documentation of quality assurance processes and standard operating procedures to ensure high-quality outputs.
  • Establish comprehensive quality metrics (e.g. F1 score, inter-annotator agreement) that align with business objectives and industry standards.
  • Continuously review and refine annotation workflows to proactively identify risks and areas to increase efficiency and reduce errors.
  • Act as the subject matter expert on annotation quality, providing ongoing feedback, training, and support to annotators and project teams to uphold the highest quality standards.

Required Skills and Qualifications

Technical Requirements

  • 3+ years of experience in data quality management, data operations, or related roles within AI/ML or data annotation environments.
  • Proven track record in designing and executing quality assurance strategies for large-scale, multi-modal data annotation projects.
  • Proven track record in a leadership role managing and developing high-performing, remote or distributed teams.
  • Deep understanding of data annotation processes, quality assurance methodologies, and statistical quality metrics (e.g., F1 score, inter-annotator agreement).
  • Strong data-analysis skills, with the ability to interrogate large datasets, perform statistical analyses, and translate findings into actionable recommendations.
  • Excellent communication skills, with experience presenting complex data and quality insights to technical and non-technical stakeholders.
  • Proficiency with annotation and QA tools.
  • High-level of proficiency in common data-analysis tools.
  • Familiarity with programmatic data analysis techniques.
  • Familiarity with the core concepts of AI/ML pipelines.

Benefits

Remote-First Flexibility

  • Work from anywhere you're most productive
  • Every challenge is new: Work on first‑of‑their‑kind problems at the frontier of AI safety.
  • Visible impact: Your architectures directly influence how the world's leading AI teams mitigate risk.
  • Room to grow: Build the solutions function from scratch and scale into leadership as revenue follows.
  • Mission‑driven team: Join sellers, researchers, and engineers united by a passion for safer AI.

Equal Opportunity Employer

Inclusive and equitable practices are our responsibility as a business. TaskUs is committed to providing equal access to opportunities.

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