AI Data Quality Architect

18 hours ago


Cabuyao, Calabarzon, Philippines beBeeData Full time ₱1,800,000 - ₱2,880,000
Job Title: AI Data Quality Architect

 

Job Description:

The ideal candidate will lead the development of high-quality annotation workflows for AI systems. They will oversee the creation and maintenance of quality assurance processes, develop metrics to measure quality, and identify areas for improvement.

About the Role:

  • Develop, refine, and document quality assurance processes and SOPs to ensure high-quality outputs.
  • Establish quality metrics (e.g., F1 score, inter-annotator agreement) that align with business objectives and industry standards.
  • Continuously review annotation workflows to identify risks and opportunities to increase efficiency and reduce errors.
  • Act as a subject matter expert on annotation quality, providing ongoing feedback, training, and support to annotators and project teams.

Analysis & Reporting:

  • Lead in-depth data analysis to diagnose quality issues, assess strategy effectiveness, and uncover root causes of recurring errors.
  • Develop dashboards for real-time quality metrics and project performance.
  • Prepare and deliver strategic quality reports to senior management and clients, outlining quality trends, risks, and improvement plans.
  • Collaborate with cross-functional teams to align on project goals and QA initiatives.

Operational Leadership:

  • Lead a team of Data Quality Analysts, providing mentorship and training to foster continuous improvement and accountability.
  • Manage configuration and integration of annotation and quality control tools to ensure optimal performance.
  • Identify and implement innovative quality control tools and automation technologies to streamline workflows and improve efficiency.

Required Qualifications:

  • 3+ years in data quality management, data operations, or related AI/ML or data annotation roles.
  • Proven experience designing and executing QA strategies for large-scale, multi-modal data annotation projects.
  • Leadership experience managing remote or distributed teams.
  • Deep understanding of data annotation processes, QA methodologies, and metrics.
  • Strong data-analysis skills and ability to translate findings into actionable recommendations.
  • Excellent communication skills with experience presenting data and quality insights to technical and non-technical stakeholders.
  • Proficiency with annotation and QA tools.
  • High proficiency in Excel and Google Sheets; familiarity with Python and SQL.
  • Familiarity with AI/ML pipelines concepts including data prep, model training, and evaluation.
  • Ability to work independently and collaboratively as part of a global team.

Benefits:

  • Remote-first flexibility: Work from anywhere you're most productive.
  • Opportunity to work on first-of-their-kind problems at the frontier of AI safety.
  • Visible impact: Your architectures influence how AI teams mitigate risk.
  • Room to grow: Build the solutions function from scratch and scale into leadership as revenue grows.
  • Mission-driven team: Collaborate with sellers, researchers, and engineers focused on safer AI.


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