Apple - Cupertino, CA
posted about 2 months ago
As the Sr. Manager of Data Quality Operations within Apple Services Engineering (ASE), you will play a pivotal role in ensuring the quality of training data used for various AI and LLM features across platforms such as the App Store, Music, and Video. This position is crucial as it involves overseeing a large network of human annotators who provide the essential training data necessary for building exceptional machine learning models. Your responsibilities will include defining what high-quality training data looks like, driving thought leadership on data quality with customers, and developing comprehensive training programs for annotators. You will also be tasked with creating 'golden datasets' that serve as benchmarks for evaluating annotator performance and scaling data collection through innovative machine learning methods. In this role, you will need to combine critical thinking, data analysis, and hands-on operations with cross-functional collaboration. The ideal candidate will possess an entrepreneurial spirit, be comfortable leading a team in a fast-paced and ambiguous environment, and have the ability to drive results. You will be responsible for creating and scaling a data innovation team that employs industry-standard methods to enhance annotation quality and increase the value of data through machine learning or AI techniques. Additionally, you will collaborate closely with project teams to address the complexities of developing high-quality training data and communicate these insights effectively to stakeholders. Your leadership will extend to managing a global workforce of over a thousand annotators, including data scientists and quality assurance teams. You will work alongside linguists, academics, and researchers to ensure that ASE remains at the forefront of data quality standards. Furthermore, you will supervise the development of training materials and curricula for the annotator base, ensuring that all team members are equipped with the knowledge and skills necessary to maintain high standards of data quality.