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ML Infrastructure Engineer - ML Compute Capacity

Apple· Machine Learning Platform Technologies
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Full-timePosted 1mo ago

About the role

Engineer on the ML Compute Capacity team responsible for designing, building, and operating production systems that optimally distribute compute resources across Apple's accelerator fleet. Focus areas include data pipelines, telemetry, observability, forecasting, and self-service tooling to scale and optimize ML compute at large scale.

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

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
  • Strong CS fundamentals
  • Bachelor's degree or higher in Engineering, Mathematics, Economics, or a related quantitative field
  • 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

Skills

Required:Distributed systems designPythonSQL / data queryingKubernetesObservability toolingData pipelines
Nice to have:GoReactCapacity planning / FinOps

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • range of discounted products and free services
  • tuition reimbursement for education related to advancing your career at Apple
  • potential discretionary bonuses or commission payments
  • relocation assistance sometimes available
  • Apple employee stock programs (discretionary RSUs, Employee Stock Purchase Plan)
Last updated Sep 18, 2026. Interested? Apply on the company site.

About Apple

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