ML Data Operations Lead, Wallet, Payment & Commerce

Would you like to contribute to Machine Learning and Generative AI technologies? Are you curious about the data that drives AI/ML success? Do you believe Machine Learning and AI can change the world? We truly believe it can! We are seeking an ML Data Operations Lead to establish and scale Data Curation, Generation and Synthesis across Wallet, Payment, and Commerce. You'll architect privacy-preserving pipelines for accelerated ML development and reduced external data dependencies. You'll work at the intersection of cutting-edge generative AI research and production ML systems, collaborating closely with Engineering, Product, Privacy, and Legal teams. This unique opportunity shapes data operations strategy, impacting features used by millions while pioneering privacy-first ML practices. As an ML Data Operations Lead, you will architect and drive the strategic vision for machine learning data operations across Wallet, Payment, & Commerce (WPC) creating robust Data pipelines that enable scalable, privacy-preserving ML solutions across multiple product initiatives. You will lead critical strategic initiatives including: Data Augmentation & Synthesis Initiative: Pioneer and drive comprehensive data synthesis initiatives to strategically reduce dependency on external data procurement, developing synthetic data generation capabilities that accelerate model development while optimizing costs and enhancing privacy protection. End-to-End ML Data Excellence: Oversee the complete lifecycle of machine learning data operations—from strategic data acquisition and advanced synthesis/augmentation to data science collaboration, annotation workflows, and rigorous data quality assurance. This role demands a visionary leader who will elevate data operations from tactical execution to strategic enablement. You will ensure that all data delivered to AI/ML models not only meets Apple's uncompromising privacy and quality standards but actively advances our leadership in privacy-first machine learning, while maintaining full compliance with regulatory and governance requirements.