Senior ML Optimization Engineer, ASE Efficiency

Apple Inc

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Quick summary

Work type: On-site
Location: Culver City, CA
Salary: $175,000–$308,500 / yr
Posted: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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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

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The Sr. ML Optimization Engineer, ASE Efficiency joins the Apple Services Engineering team to improve cloud service efficiency and resource utilization. This role involves analyzing infrastructure usage patterns and performing 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. Key responsibilities include developing cost models, creating reusable software tooling, and collaborating with SRE teams and data scientists. The position requires a strong software engineering background, experience with ML-based modeling, time-series forecasting, and platform observability tools. You will apply classical optimization techniques and machine learning pipelines to solve complex infrastructure problems, directly influencing the unit cost of services and overall performance across large-scale cloud environments.

Skills

Machine Learning Time-series Forecasting Capacity Planning Resource Optimization Distributed Systems Platform Observability Optimization Techniques Cloud Infrastructure SRE

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.
Formulate and solve large-scale optimization problems to allocate capacity and schedule workloads.
Minimize operational costs while maintaining specific 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.
Exceptional analytical and problem-solving skills with the ability to communicate complex ideas to cross-functional teams.
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.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experience applying classical optimization techniques to real-world systems or infrastructure problems (preferred).
PhD in CS or related field with a focus on machine learning, optimization, or large-scale distributed systems (preferred).

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