Engineering Program Manager, Ai/ml, Apple Services Engineering (ase)

Apple Apple · Big Tech · Cupertino, CA · Software and Services

Engineering Program Manager for AI/ML and Generative AI features within Apple Media Products. This role involves driving the end-to-end delivery of large-scale, cross-functional ML/GenAI programs, from strategic planning and execution to managing timelines, resources, and cross-functional collaboration. The role requires understanding the full ML lifecycle and mitigating technical challenges to ensure successful product launches.

What you'd actually do

  1. Drive technical scoping, effort estimation, and resource allocation discussions with engineering, research, and cross-functional teams to ensure realistic and achievable roadmaps.
  2. Translate high-level GenAI/ML product vision and research goals into detailed, actionable engineering roadmaps and technical execution plans. This involves defining technical scope, breaking down complex initiatives into manageable phases, identifying key engineering deliverables, and ensuring alignment across ML Engineering, Data Engineering, and Platform teams.
  3. Drive the end-to-end engineering execution of GenAI/ML initiatives. This includes orchestrating efforts across specialized engineering teams (ML, Data, Platform, SRE), tracking progress against technical milestones, facilitating technical decision-making, coordinating launch and managing post launch improvements.
  4. Proactively identify, analyze, and mitigate technical blockers, architectural challenges, and inter-team dependencies inherent in GenAI/ML development (e.g., data quality issues, compute resource contention, model scalability, integration complexities). Develop contingency plans and drive resolution to keep engineering programs on track.
  5. Facilitate clear, concise, and effective technical communication across diverse engineering teams and with relevant stakeholders (Product, Research, Leadership). Articulate complex engineering progress, technical trade-offs, challenges, and proposed solutions, ensuring alignment, informed decision-making, and transparency throughout the program lifecycle.

Skills

Required

  • 5+ years of program management experience, including experience taking features through the complete software development life cycle with multiple stakeholders
  • Demonstrated experience managing end-to-end Machine Learning projects. This includes understanding the full ML lifecycle from data acquisition, feature engineering, model training, evaluation, deployment, monitoring, and iterative improvement.
  • BA/BS in Computer Science, Computer Engineering, or similar field or relevant industry experience

Nice to have

  • Experience to execute cross-functional and cross-organization project management - ability to work across diverse teams, navigate organizational landscape, build relationships and drive project delivery
  • Ability to understand and extract action plans from complex technical discussions & translate into succinct messaging for multi-functional and executive status reporting
  • Built global products by collaborating across Product, Engineering, Data Sciences, Analytics, Design and other key partners
  • Consistent track record of shipping complex customer-facing and backend engineering projects under demanding timelines
  • Strong facilitation skills (requirements sessions, design meetings, progress and status meetings)
  • Best-in-class communication and presentation skills (written & verbal) to all levels of an organization
  • Be able to work with ambiguity, organize & create order

What the JD emphasized

  • Drive the end-to-end delivery of large-scale, cross-functional Machine Learning (ML) and Generative AI (GenAI) programs and features
  • Lead the strategic planning, execution, and delivery of multiple concurrent ML/GenAI features
  • Drive the end-to-end engineering execution of GenAI/ML initiatives
  • Proactively identify, analyze, and mitigate technical blockers, architectural challenges, and inter-team dependencies inherent in GenAI/ML development
  • Demonstrated experience managing end-to-end Machine Learning projects
  • shipping complex customer-facing and backend engineering projects

Other signals

  • Drive the end-to-end delivery of large-scale, cross-functional Machine Learning (ML) and Generative AI (GenAI) programs and features within Apple Media Products (AMP).
  • Lead the strategic planning, execution, and delivery of multiple concurrent ML/GenAI features, encompassing scope definition, requirements gathering, timeline management, and resource allocation.
  • Drive the end-to-end engineering execution of GenAI/ML initiatives. This includes orchestrating efforts across specialized engineering teams (ML, Data, Platform, SRE), tracking progress against technical milestones, facilitating technical decision-making, coordinating launch and managing post launch improvements.
  • Proactively identify, analyze, and mitigate technical blockers, architectural challenges, and inter-team dependencies inherent in GenAI/ML development (e.g., data quality issues, compute resource contention, model scalability, integration complexities).
  • Demonstrated experience managing end-to-end Machine Learning projects. This includes understanding the full ML lifecycle from data acquisition, feature engineering, model training, evaluation, deployment, monitoring, and iterative improvement.