This role pays more than
84%
of similar roles. Most pay
$154,850–$226,350
— the shaded band above.
At the midpoint, this role pays about
$244k
versus about
$191k
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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 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 evolving governance tooling for compute resource requests and utilization data. The individual 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 and foundation models. Required skills include SQL, Python for data analysis, and experience with Tableau or Grafana. The role addresses the critical challenge of managing complex machine learning compute lifecycles, ensuring efficient resource allocation and infrastructure savings across large-scale ML ecosystems.
Design and manage a multi-tiered, scalable hub-and-spoke support model for technical escalations.
Develop governance tools to capture accurate data on compute resource requests, allocations, and utilization.
Manage the transition 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 handle large-scale machine learning demands.
Produce strategic analyses to inform executive decisions regarding ML compute investment and allocation.
What we're looking for
Bachelor's degree 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 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 engineers and executives.
Familiarity with ML training infrastructure concepts such as GPU utilization and scheduling efficiency.
Generative AI
Agentic AI
Large Language Models
LLMs
SQL
Oracle
Microsoft SQL Server
Salesforce
Kafka
Cloud Computing
Virtualization
System Administration
Configuration Management
Cybersecurity
FinOps
NIST AI Risk Management Framework