AI/ML - Technical Program Manager, Data Platform Efficiency


Saeattle, Washington, United States

Full time

Project Management

May 5

As a member of the AI/ML Data Products & Platforms Engineering Program Management (EPM) group, you will improve and enhance the quality of Apple AI/ML features for hundreds of millions of users around the world. You'll devise creative solutions for scaling quality assurance for a multi-platform, global, and rapidly evolving product. You'll partner with AI/ML's Data Platform group to help realize our vision: build a world-class infrastructure while following the extraordinary privacy and security requirements of Apple.

Join us, and impact hundreds of millions of customers across a plethora of Apple of devices! We develop scalable, reliable, and privacy-first enterprise data infrastructure services. Our ultimate goal: empowering all data users at Apple to measure and improve Apple products powered by Artificial Intelligence and Machine Learning (Siri, Search and more). To help us accomplish this mission, we're looking for an experienced hands-on Technical Program Manager with a proven track record supervising sophisticated and highly-leveraged data infrastructure products. You'll collaborate with and coordinate teams of versatile and creative backend Software Engineers too.

Key Qualifications

  • 8+ years project management, engineering management, and/or QA/QC engineering management experience for software development quality in a fast-paced, incredibly complex service
  • Prior data analysis experience (SQL, Python/Jupyter Notebooks, Tableau, Superset, Strong Pivot-Table-Fu), and experience crafting data-driven project-management frameworks
  • Technical project management or engineering ownership of cloud & data infrastructure used by external engineering and data analytics or science teams
  • Experience gathering, analyzing, and presenting metrics to back up assumptions, make recommendations, and drive actions
  • Examples throughout your career of hands-on involvement in delivering data infrastructure products and tools that are used by engineering teams to improve customer experience
  • Self-motivated, independent, and proactive; demonstrated creative and critical thinking capabilities
  • You can quickly triage, prioritize, and lead under pressure
  • Outstanding communication and presentation abilities, written and verbal, to all levels of an organization


- Drive AI/ML’s privacy-first Data Platform Efficiency program; streamlining processes, crafting frameworks that scale across different teams, and supporting safe and continuous/agile development and release

- Design, build and operate processes to ensure partners have dependable usage-reporting (at the granularity required to make tough decisions), submit usable forecasts to inform budget creation and management, and provide good guidance on progress vs. budget to XF Finance and Operations teams

- Own monthly close and quarterly-close processes; including forecasts of future growth in usage. Identify recommendations for efficiency-gains, to help Engineering, efficiency program offices, and Finance have the insight needed to make decisions

- Partner with Engineering to build a process for efficiency-project identification; including: opportunity assessment, scoping, and funding to deliver on efficiency savings for Apple and AI/ML

- Partner with Engineering to product manage high-efficiency technical projects and drive adoption of those projects across partner teams to realize project goals (e.g. cost, speed, etc.)

- Facilitate XF communication with other teams inside and outside of the Data Platform organization. Ensure requirements are well understood and that priorities and delivery expectations are aligned

- Establish relationships across AI/ML; educating teams on the right way to ship the finest software possible and facilitating communication between cross-divisional groups

Education & Experience

BS/MS EE/CS/CE or equivalent in Statistics, Computer Science, or Economics (with strong data analysis focus)

Additional Requirements

  • - Technical understanding of different components of modern big data infrastructure; such as Spark, Kafka, Kubernetes, Flink, Hadoop ecosystem, etc.
  • - Experience with financial reporting and reconciliation processes
  • - Experience with AWS products such as S3, EC2, EKS, IAM, RDS, etc.

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