Senior Manager of Quality Assurance, AIML Data Operations

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences - quickly. The AIML team is looking for a passionate, detail-obsessed Senior Manager of Quality Assurance to lead the QA function within our Data Annotation operations. This is a rare opportunity to directly shape the quality standards that underpin the intelligent systems used by hundreds of millions of people every day.

You will lead a team of QA professionals, define and defend data quality standards, and champion a culture of rigorous, scalable quality assurance across global annotation workflows. If you thrive at the intersection of operational excellence, data quality, and cross-functional leadership - this role was built for you.

As Senior Manager of QA for Data Annotation, you will own the end-to-end quality assurance strategy for annotation pipelines that feed directly into Apple's AI and machine learning models. You will partner closely with Data Science, Engineering, and Operations leadership to ensure that data quality is not an afterthought - it is a foundation. You will manage and develop a team of QA specialists and leads, set clear quality metrics, and build scalable processes that grow with our annotation programs.

Your decisions will have measurable, real-world impact on the performance of Apple Intelligence products.

Master's degree or advanced certification in a relevant discipline

Experience with annotation platforms and QA tooling (e.g., Label Studio, Scale AI, Surge, Toloka, or similar) Familiarity with inter-annotator agreement methodologies (Cohen's Kappa, Krippendorff's Alpha, etc.) Experience managing QA for multilingual or multimodal annotation datasets Track record of building or scaling QA programs in a globally distributed, vendor-augmented operating model Passion for Apple Intelligence products and a deep appreciation for the role of data quality in user experience

Experience with statistical sampling techniques and quality auditing frameworks Familiarity with RLHF (Reinforcement Learning from Human Feedback) data workflows

Bachelor's degree in a relevant field (Computer Science, Linguistics, Data Science, Operations, or equivalent) 8+ years of experience in quality assurance, data operations, or a related field 10+ years of people management experience leading QA or data operations teams Demonstrated experience defining and operating QA programs for data annotation or content labeling at scale Solid understanding of AIML concepts, with practical knowledge of how data quality affects model performance Strong analytical skills with experience using data to measure, communicate, and drive quality improvements Professional fluency in English;

excellent written and verbal communication skills across all levels of an organization Ability to travel internationally when required