About The Position

Apple is seeking a Senior Engineering Program Manager to lead highly cross-functional software and machine learning initiatives for Apple Intelligence evaluations. The role owns evaluation plans for Apple foundation models or AI features built on them, partnering with teams across Research, Engineering, Privacy, and Data Science. The work helps ensure products serving more than 1 billion customers meet Apple’s quality expectations. The position involves defining evaluation scope, metrics, timelines, and launch-readiness criteria; coordinating concurrent workstreams; and managing evaluation annotation and data collection operations. The program manager also works with Engineering, Privacy, and Legal on data strategy, and communicates technical complexity clearly to executive leadership.

Requirements

  • Bachelor’s or master’s degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent.
  • At least 5 years of experience managing large-scale, ML-powered and software programs across large organizations.
  • Proven program management, analytical, and cross-functional leadership skills.
  • Experience driving data-driven decision-making and process improvements.
  • Excellent written and verbal communication skills, including presentation and negotiation, and the ability to communicate abstract ideas clearly.
  • Strong problem-solving skills and attention to detail.
  • Experience analyzing product data to assess quality and identify opportunities.
  • Ability to work in a fast-paced, ambiguous environment, with curiosity and the ability to quickly learn new technical concepts.
  • Solid understanding of how machine learning systems are built, evaluated, and released.

Nice To Haves

  • Direct program management experience with Generative AI or Large Language Models (LLMs).
  • Familiarity with LLM evaluation practices.
  • Experience shipping AI features in a consumer product.

Responsibilities

  • Own evaluation plans for foundation models or AI features, including scope, metrics, timelines, and launch-readiness criteria.
  • Partner with Product, Research, Data Science, and Engineering teams to define evaluation requirements, methodologies, and tooling.
  • Drive multiple complex workstreams, clarify dependencies and critical paths, manage risks, resolve conflicts, and keep stakeholders aligned.
  • Manage annotation and data collection operations to deliver high-quality evaluation data on schedule.
  • Partner with Engineering, Privacy, and Legal teams to ensure the data strategy aligns with Apple’s core values.
  • Synthesize technical complexity into clear, actionable communications for executive leadership.
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