Senior ML Optimization Engineer, ASE Efficiency

Apple Inc

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Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$175,000–$308,500 / yr
Posted
4 days ago
Freshness
Confirmed live today

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Competitive pay

How this pay compares to similar roles

Similar $225k
This role $242k
$159k $325k
below market most similar roles pay here above market

This role pays more than 62% of similar roles. Most pay $194,500–$254,750 — the blue band above. At the midpoint, this role pays about $242k versus about $225k for comparable roles.

Based on 240 similar postings.

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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.

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At a glance

TL;DR · Senior ML Optimization Engineer, ASE Efficiency

The Sr. ML Optimization Engineer, ASE Efficiency joins the Apple Services Engineering team to improve cloud service efficiency and resource utilization. In this role, you will perform in-depth analysis of infrastructure usage patterns and data-driven capacity planning to ensure scalability while minimizing waste. You will formulate and solve large-scale optimization problems to allocate capacity, schedule workloads, and minimize costs under reliability and latency constraints. Your daily work involves connecting application demand to infrastructure requirements and integrating solutions into reusable software and tooling. You will utilize machine learning-based modeling, time-series forecasting, and platform observability tools to develop cost models. The role focuses on solving technical problems related to cloud sustainability, service performance, and resource optimization across large-scale distributed systems and cloud infrastructures.

What you'll do

  • Optimize the design, deployment, and operation of services across Apple Services Engineering.
  • Analyze infrastructure usage patterns to perform data-driven capacity planning for scalability and reliability.
  • Connect application and business demand to specific infrastructure requirements.
  • Formulate and solve large-scale optimization problems to allocate capacity and schedule workloads.
  • Minimize operational costs while maintaining strict reliability and latency constraints.
  • Integrate optimization solutions into reusable software and internal tooling.
  • Develop cost models and strategies to ensure optimal resource utilization for software services.
  • Use platform observability tools to gain deep insights into service performance and drive optimizations.

What we're looking for

  • 3+ years of relevant experience in large-scale cloud services or similar environments.
  • Strong software engineering background with experience in ML-based modeling, time-series forecasting, and data-driven decision making.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Hands-on experience with platform observability tools to gain insights into service performance.
  • Experience developing cost models and strategies for software services to ensure optimal resource utilization.
  • Exceptional analytical and problem-solving skills with the ability to communicate complex ideas to cross-functional teams.
  • Experience applying classical optimization techniques to real-world systems or infrastructure problems (preferred).
  • Demonstrable experience in capacity planning and resource optimization using machine learning and/or optimization techniques (preferred).

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