ML Infrastructure Engineer - ML Compute Capacity

Apple Inc.; Santa Clara, Northern (CA, KY); Hybrid; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. is seeking a seasoned engineer for ML Compute Capacity, designing and operating production systems that optimally distribute compute resources across Apple’s accelerator fleet.

You will work across data pipelines, APIs, and dashboards to deliver real-time fleet health insights and cost optimization. The role emphasizes autonomy in a fast-paced environment, with responsibilities spanning data models, telemetry, forecasting, and cross-functional collaboration to balance usability and

Qualifications

• 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 data.
• Experience with observability tools (Prometheus, Grafana) or equivalent monitoring systems.
• Bachelor's degree or higher in Engineering, Mathematics, Economics, or related quantitative field.

Responsibilities

• Build and operate demand and capacity planning systems.
• Build data pipelines and telemetry systems ingesting fleet-wide utilization and cost data.
• Develop observability infrastructure—monitoring, alerting, dashboards—for fleet health and efficiency.
• Drive forecasting, optimization, and supply chain tooling at scale.
• Create end-to-end tooling from data models to dashboards for leadership insights.
• Build self-service platforms with schemas and APIs for ML teams, infra engineers, and finance.
• Engage cross-functionally with finance, supply chain, data center ops, and more.
• Support the team through code reviews and knowledge sharing.

Skills

Python

Go

Data pipelines

Observability

Distributed systems

Education

Bachelor's degree or higher in Engineering, Mathematics, Economics, or related quantitative field

Tools

Trino

PostgreSQL

Elasticsearch

Prometheus

Grafana

Kubernetes

React

Job description

Santa Clara, California, United States Machine Learning and AI

Scaling machine learning workloads across thousands of accelerators creates challenges that few engineers ever encounter. In Apple’s Machine Learning Platform Technologies organization, we build the infrastructure that powers large-scale ML training and inference workloads, bringing together expertise in distributed systems, machine learning infrastructure, and high-performance computing.

Description

As an engineer on the ML Compute Capacity team, you will design, build, and operate the production systems that ensure compute resources are optimally distributed throughout the company. You'll work across the stack — from data pipelines and backend services to APIs and interactive frontends — developing telemetry systems, optimization algorithms, policies, and intuitive tools for managing demand and improving efficiency across Apple's largest accelerator fleet. Our small, nimble team works in a high-autonomy, fast-paced environment, and we're passionate about digging into data patterns, laying out the performance characteristics of an entire distributed system, and knowledge sharing. If the opportunity to own and operate services that scale, stay highly available, and "just work" excites you, then please reach out to us!

Responsibilities

• Build and operate demand and capacity planning systems
• Build data pipelines and telemetry systems that ingest, normalize, and serve fleet-wide utilization and cost data across multi-tenant and heterogeneous fleets
• Develop observability infrastructure — monitoring, alerting, and dashboards — that surfaces real-time fleet health and efficiency signals
• Drive innovation in forecasting, optimization, and supply chain management tooling that works at scale
• Build end-to-end tooling — from data models and APIs to interactive dashboards — that distills complex data into actionable insights for leadership
• Build self-service platforms with well-defined schema contracts and APIs, enabling ML teams, infrastructure engineers, and finance to balance usability, utilization, and costs
• Engage cross-functionally with finance analysts, supply chain managers, data center operations, compute infrastructure engineers, and more
• Support the team through code reviews and knowledge sharing

Minimum Qualifications

• 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 (e.g., Trino, PostgreSQL, Elasticsearch)
• Experience with observability tools (e.g., Prometheus, Grafana) or equivalent monitoring systems
• Excellent problem-framing and problem-solving skills
• Bachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative field

Preferred Qualifications

• Experience operating Kubernetes at production scale — including scheduling, resource management, and cluster debugging
• Experience with modern web frameworks like React
• Familiarity with accelerator utilization patterns across ML training and inference
• Strong interest with capacity planning, cost attribution, or FinOps systems

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.