ML Infrastructure Engineer – Capacity & Telemetry

Apple; Santa Clara (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Apple is seeking an experienced ML infrastructure engineer to scale and operate production systems for large-scale ML training and inference. You will design data pipelines, observability, and tooling across a multi-tenant fleet, collaborating with finance, data center operations, and engineering teams.

The role emphasizes capacity planning, forecasting, and cost attribution, with a focus on building self-service platforms and scalable services that stay highly available.

Qualifications

• 7+ years of experience in machine learning infrastructure and distributed systems.
• Experience with ML infrastructure on GPUs or TPUs.
• Proficiency in Python and/or Go for production backend and data engineering.
• Experience building data pipelines and queries over large-scale data (Trino, PostgreSQL, Elasticsearch).
• Experience with observability tools (Prometheus, Grafana) or equivalents.
• Excellent problem-framing and problem-solving skills.
• Strong CS fundamentals.
• Bachelor's degree or higher in Engineering, Mathematics, Economics, or related quantitative field.

Responsibilities

• Build and operate demand and capacity planning systems.
• Develop data pipelines and telemetry systems that ingest, normalize, and serve fleet-wide utilization and cost data.
• Develop observability infrastructure — monitoring, alerting, and dashboards.
• Drive forecasting, optimization, and supply chain tooling at scale.
• Build end-to-end tooling — from data models and APIs to dashboards.
• Build self-service platforms with well-defined schema contracts and APIs.
• Engage cross-functionally with finance, data center operations, and infra teams.
• Support the team through code reviews and knowledge sharing.

Skills

Python

Go

Data pipelines

Distributed systems

Observability

Problem solving

CS fundamentals

Education

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

Tools

Trino

PostgreSQL

Elasticsearch

Prometheus

Grafana

Kubernetes

React

Job description

Apple is seeking an experienced ML infrastructure engineer to scale and operate production systems for large-scale ML training and inference. You will design data pipelines, observability, and tooling across a multi-tenant fleet, collaborating with finance, data center operations, and engineering teams.

The role emphasizes capacity planning, forecasting, and cost attribution, with a focus on building self-service platforms and scalable services that stay highly available.