Engineering Program Manager, AI and Data Platform, Apple Services Engineering

Are you ready to take a pivotal role in shaping Apple's next-generation products by driving the adoption of machine learning and equipping engineering teams with robust data insights? Join the Apple Cloud AI Platform EPM team as a Senior Program Manager, focusing on Machine Learning Infrastructure and data platform products. You'll play a critical role in shaping and scaling the platform that powers AI application development across Apple.

The Apple Cloud AI Platform team powers GenAI, ML, data analytics, and exploration platforms that fuel the App Store, Music, Search, Maps, iCloud and many other beloved products in the Apple ecosystem. Our mission is to provide ML engineers and data scientists with an innovative, reliable, secure, and user-friendly platform for ingesting, storing, processing, and interacting with data, ultimately helping teams derive insights that drive product success. In this role, you'll oversee a platform responsible for secure data ingestion, storage, management, feature engineering, real-time and batch processing, data transformation, and analytics, among other critical functions. This infrastructure enables Apple's engineering teams to manage the ML lifecycle effectively, supporting model training and enhancing product quality to deliver a seamless, privacy-centric experience to Apple customers. You'll collaborate extensively with cross-functional partners within and beyond the AI/ML landscape, defining and delivering impactful ML and data platform products that meet Apple's organizational needs. With a deep understanding of user needs, you'll own complex challenges, exploring all facets of business opportunities, and connecting insights across roles and functions to drive innovative solutions.Drive Program Roadmap and Strategy: Define and execute the roadmap for scalable, privacy-preserving ML infrastructure and data platforms, empowering Apple's development teams to efficiently ingest, store, process, transform, and analyze data for machine learning and analytics. Program Ownership and Use Case Identification: Proactively engage with internal partners to identify high-impact use cases, build strong business cases, and define detailed requirements and product specifications.Lead cross-functional discussions with stakeholders to prioritize and establish a strategic program roadmap. Establish and Maintain Feedback Loops: Develop and sustain a robust feedback loop with stakeholders, partners, and users to drive iterative improvements, ensuring that products continuously evolve to meet user needs and program objectives. Define Success Metrics: Develop and monitor key product metrics that align with broader ASE product goals, enabling clear measurement of AI/data platform success and impact. Champion Product Adoption and Evangelism: Act as a primary advocate for data products, leading efforts to promote platform adoption, ensuring awareness, and aligning stakeholders on the platform's value across the organization. Foster Cross-Functional Relationships: Build strong, collaborative relationships across Apple, facilitating seamless communication between divisions and fostering a unified approach to program goals. Lead Complex Multi-Org Programs: Identify and manage stakeholders, dependencies, risks, and tradeoffs across distributed ML systems spanning engineering, infrastructure, product, security, privacy, regulatory, and governance teamsProgram management in ML Infrastructure: 7+ years of experience leading large cross-functional infrastructure programs, with 2+ years leading ML, AI, and data programs. Proven Delivery of Large-Scale Solutions: Demonstrated success in delivering reliable, large-scale ML infrastructure and data platform products, including data storage, feature store, data management, data versioning, privacy, governance, analytics, and backend services that support high-throughput, user-facing applications. Technical Expertise in Cloud and Hybrid Platforms: Solid understanding of cloud technologies and experience in building hybrid cloud ML infrastructure and data platforms. BS in Computer Science, Computer Engineering, or related technical field OR relevant industry experienceUser-Centric Program Strategy: Passionate about optimizing the user experience, providing thought leadership to enhance end-to-end user interactions for technical products. Technical Proficiency in ML and Data Tools: Familiarity with ML infrastructure, Agentic AI skills, frameworks like PyTorch and TensorFlow, Jupyter notebooks, Spark, Trino, Flink, SQL, Python, and other advanced analytical tools is a significant asset. Familiarity with Distributed Cloud ML Systems: Familiarity with distributed systems and large-scale compute environments. Background working closely with applied Data & ML infra teams. Experience with developer platforms, APIs, or infrastructure products.