This role pays more than
81%
of similar roles. Most pay
$155,900–$232,750
— the shaded band above.
At the midpoint, this role pays about
$244k
versus about
$194k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1961 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1589 roles with salary data.
Governance & Operations Lead, Infrastructure & Planning joins the Platform Acceleration & Compute Efficiency team to build and own the governance and operations function from the ground up. This role involves designing a scalable hub-and-spoke support model, managing tiered engineering escalation groups, and overseeing governance tooling for compute resource requests and utilization data. The successful candidate will partner with analytics leads to develop telemetry frameworks, dashboards, and automated alerts that identify system anomalies and translate technical metrics into financial impact models. Key responsibilities include bridging coverage gaps across diverse hardware like GPUs and TPUs while optimizing inference workloads. Required skills include SQL, Python for data analysis, and experience with Tableau, Looker, or Grafana. The role addresses the critical challenge of managing the machine learning ecosystem by ensuring efficient, scalable compute and infrastructure for large-scale model development.
Design and manage a multi-tiered, scalable hub-and-spoke support model for technical escalations.
Develop governance tools to capture and track compute resource requests, allocations, and utilization data.
Manage the expansion of ML workloads across diverse hardware including GPUs, TPUs, and custom silicon.
Build dashboards, automated alerts, and analytical models to identify infrastructure efficiency opportunities.
Identify system anomalies and bottlenecks to create financial impact models for executive leadership.
Provide data-driven analytics to engineering teams to optimize foundation models and inference workloads.
Create automated governance processes specifically designed to meet large-scale machine learning demands.
Produce strategic analyses to inform executive decisions on ML compute investment and infrastructure strategy.
What we're looking for
BS in Computer Science, Data Science, Computer Engineering, or equivalent practical experience.
5+ years of experience in governance/operations, data engineering, analytics engineering, technical program management, or large-scale compute environments.
Proven experience designing and operating complex systems and processes from the ground up.
Direct experience managing SRE and hierarchical technical support systems.
Proficiency in SQL and building analytical dashboards or data products using tools like Tableau, Looker, or Grafana.
Experience designing data models or telemetry schemas for infrastructure, capacity, or utilization data.
Ability to translate raw technical metrics into clear business narratives for both engineers and executives.
AI fluency and experience with Python for data analysis or pipeline development (preferred); familiarity with ML training infrastructure and FinOps (preferred).