Senior ML Data Program Manager

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Company: Apple

Location: Cupertino, CA 95014

Description:

Summary
Would you like to contribute to generative AI and transform how people interact with AI technologies? Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the Machine Learning Operations Data Team, part of Intelligent System Experience (ISE) group within the software engineering organization at Apple. We are responsible for building high-quality ML datasets at scale, used to train ML models that power AI-centric features for many Apple products (iPhone, iPad, Mac, Apple Watch, and even AirPods). Such features as Apple Intelligence, face recognition of your loved ones in your Photos app, and input experiences (e.g., autocorrect, next-word prediction, handwriting recognition) are all features our team has supported.

We are looking for a talented individual to drive Data Programs supporting ML features, in close collaboration with our R&D partners, and to run the corresponding data projects end-to-end (collection & annotation). We invite you to join us at this exciting time! Grow fast and positively impact multiple critical features on your first day at Apple!

Description
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. Apple's 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 Apple's 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

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