About The Position

Imagine the contributions you can make at Apple. New insights have a way of becoming great products, services, and customer experiences very quickly. Passion and dedication are the keys to the accomplishments you can make here! We are seeking a Manager, Data Quality Assurance to lead a team responsible for designing and implementing quality frameworks for data used in AIML model training and evaluation. This role manages a group of Quality Engineers and Quality Program Managers who develop processes, metrics, and tooling to ensure the accuracy, consistency, and reliability of annotation data at scale. You will work closely with Engineering, Data Science, Training, and Production Operations teams to integrate quality controls into data pipelines, build automated quality validation systems, and drive continuous improvements in data quality. The ideal candidate is a strong people leader who thrives in fast-paced environments and enjoys solving complex quality challenges in large-scale data systems.

Requirements

  • BS or MS in data science, computer science, statistics, or related technical fields.
  • 6+ years of experience in data operations, data quality, annotation systems, or machine learning data pipelines.
  • 2+ years of people management experience leading technical or operational teams.
  • Experience designing or operating data quality frameworks or evaluation methodologies.
  • Experience working cross-functionally with engineering, data science, and operations teams.
  • Strong analytical and problem-solving skills with the ability to translate data insights into operational improvements.
  • Excellent communication and stakeholder management skills.

Nice To Haves

  • Experience with large-scale annotation or human-in-the-loop ML systems.
  • Familiarity with machine learning training data workflows and evaluation methodologies.
  • Experience implementing automated quality validation or AI-assisted QA systems.
  • Experience managing quality initiatives across large vendor or distributed workforces.
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