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

Are you ready to take a pivotal role in shaping Apples 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. Youll play a critical role in shaping and scaling the platform that powers AI application development across Apple. nnThe 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 youll 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 Apples 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. Youll collaborate extensively with cross-functional partners within and beyond the AI/ML landscape defining and delivering impactful ML and data platform products that meet Apples organizational needs. With a deep understanding of user needs youll 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 Apples development teams to efficiently ingest store process transform and analyze data for machine learning and 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 cross-functional discussions with stakeholders to prioritize and establish a strategic program 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 Success Metrics: Develop and monitor key product metrics that align with broader ASE product goals enabling clear measurement of AI/data platform success and 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 platforms value across the Cross-Functional Relationships: Build strong collaborative relationships across Apple facilitating seamless communication between divisions and fostering a unified approach to program 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 teams

Program management in ML Infrastructure: 7 years of experience leading large cross-functional infrastructure programs with 2 years leading ML AI and data 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 Expertise in Cloud and Hybrid Platforms: Solid understanding of cloud technologies and experience in building hybrid cloud ML infrastructure and data in Computer Science Computer Engineering or related technical field OR relevant industry experience

User-Centric Program Strategy: Passionate about optimizing the user experience providing thought leadership to enhance end-to-end user interactions for 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 with Distributed Cloud ML Systems: Familiarity with distributed systems and large-scale compute environments. Background working closely with applied Data u0026 ML infra teams. Experience with developer platforms APIs or infrastructure products.