Our MLO Data team focuses on data acquisition data synthesis data science annotation and data QA. Each year we power dozens of features and work closely with ML teams across the Software Organization. Apples commitment to deliver incredible experiences to a global and diverse set of users in full respect of their privacy leads our team to explore innovative ways of collecting and annotating data. This role is responsible for overseeing the end-to-end process for our R&D partners machine learning data needs; from conceptualization to completion and ensuring that the data delivered to R&D meets Apples rigorous quality standards. This includes:- Collaborate with R&D partners to understand and define their data requirements from inception to delivery- Design and implement ML Data Ops strategies optimized for each feature (collection and annotation) including the identification and sourcing or creation of necessary tooling equipment or crowd- Drive enhancements of data operations (increase scalability diversity and quality reduce cost and lead time) through innovative workflows that combine human and machine computation (leveraging capabilities of ML and foundation models)- Work closely with privacy legal procurement and product security teams to identify and clear options considered for data operations- Thoroughly scope projects estimating timelines cost and identifying potential challenges in advance- Coordinate data programs across internal data functions (data engineering QA) and other partners- Establish clear guidelines and training material- Collaborate with vendors to ensure tasks are calibrated appropriately; track and report on quantity and quality metrics
Bachelors degree in computer science or related field; or equivalent practical experience.
5 years of experience with program/project management.
Exhibits excellent program/project management communication interpersonal analytical and organizational skills
A talent for creating ML datasets focusing on end-to-end user experience by foreseeing issues handling edge cases and removing bias while ensuring inclusion and fairness
Proficient in problem-solving and critical thinking with a focus on innovation and continuous improvement
Scripting skills (Python) to automate tasks compute metrics and explore use of workflows combining ML and human inputs
Self-starter able to handle ambiguity identify risks troubleshoot and find the right people and tools to get the job done
Capacity to multitask and manage multiple projects in parallel while meeting deadlines and maintaining clear and effective communication with stakeholders
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