below marketmost similar roles pay hereabove market
This role pays more than
85%
of similar roles. Most pay
$184,613–$254,750
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$220k
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
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
JOB TITLE: ML Infrastructure Engineer - ML Compute Capacity
The ML Infrastructure Engineer - ML Compute Capacity joins the Machine Learning Platform Technologies organization to design, build, and operate production systems for optimal compute resource distribution. This role involves developing demand and capacity planning systems, data pipelines, and telemetry systems to ingest and serve fleet-wide utilization and cost data across multi-tenant, heterogeneous fleets. You will build observability infrastructure, forecasting tools, and self-service platforms with well-defined schema contracts and APIs. Key technologies include Python, Go, Trino, PostgreSQL, Elasticsearch, Prometheus, Grafana, and React. The work focuses on managing large-scale ML training and inference workloads by solving complex problems in capacity planning, cost attribution, and supply chain management for a massive accelerator fleet, ensuring high availability and efficiency across distributed systems.
Build and operate demand and capacity planning systems for large-scale ML workloads.
Develop data pipelines and telemetry systems to ingest and serve fleet-wide utilization and cost data.
Create observability infrastructure including monitoring, alerting, and dashboards for real-time fleet health.
Drive innovation in forecasting, optimization, and supply chain management tooling at scale.
Build end-to-end tooling from data models and APIs to interactive dashboards for leadership insights.
Develop self-service platforms with well-defined schema contracts and APIs for ML and finance teams.
What we're looking for
7+ years of experience in relevant areas.
Experience with machine learning infrastructure on GPUs or TPUs.
Proficiency in Python and/or Go for production backend and data engineering work.
Experience building data pipelines and crafting robust queries over large-scale, multi-source data.
Experience with observability tools like Prometheus and Grafana or equivalent monitoring systems.
Strong CS fundamentals and excellent problem-solving skills.
Bachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative field.
Experience operating Kubernetes at production scale, modern web frameworks like React, and familiarity with accelerator utilization patterns (preferred).
Python
Go
C++
Kubernetes
Ray
PyTorch
JAX
TensorFlow
vLLM
Pathways
GPU
TPU
Distributed Systems
Container Orchestration
Performance Engineering
Model Serving
Cloud Infrastructure