Sr. ML Optimization Engineer, iCloud

Apple Inc.; Cupertino (CA); On-site; USD 181,100 - 318,400; Full time

Benefits offered by this job

Comprehensive medical and dental coverage

Employee Stock Purchase Plan with discounts

Reimbursement for educational expenses

Job summary

Apple Inc. in Cupertino, California, is seeking a Sr. ML Optimization Engineer to enhance the efficiency of its cloud services. This role involves analyzing infrastructure usage and implementing data-driven capacity planning. The ideal candidate will have at least 3 years of experience in large-scale cloud services, a background in machine learning, and strong problem-solving skills. The position offers a competitive salary range of $181,100 to $318,400, along with comprehensive benefits including stock options, medical coverage, and professional development reimbursement.

Qualifications

• 3+ years of relevant experience in large‑scale cloud services.
• Strong background and experience in ML-based modeling and forecasting.
• Exceptional analytical and problem-solving skills.

Responsibilities

• Help optimize the design and operation of iCloud services.
• Collaborate with engineering teams to develop and implement strategies.
• Formulate large-scale optimization problems to minimize costs.

Skills

Large-scale cloud services analysis

ML-based modeling

Time-series forecasting

Cost models development

Analytical problem-solving

Education

Bachelor or Master’s degree in Computer Science or related field

Tools

Platform observability tools

Job description

Cupertino, California, United States Software and Services

In Apple’s iCloud services organization, efficiency is not just a technical goal; it's an essential part of our commitment to environmental sustainability and optimal resource utilization. This team plays a pivotal role in ensuring that our cloud services are not only robust and reliable but also efficiently utilize resources at scale. This team also focuses on ML-driven forecasting, capacity planning, resource optimization, and the development of sophisticated cost models for iCloud's large-scale services. As a Sr. ML Optimization Engineer, you will work at the intersection of systems engineering, infrastructure strategy, applied analytics, machine learning, and large-scale optimization. You will have the unique opportunity to collaborate closely with experts, contribute to cutting‑edge forecasting and optimization strategies, and directly impact millions of users globally. Our team is at the forefront of driving efficiency in one of the world’s largest cloud infrastructures, supporting billions of devices globally.

Description

The Sr. ML Optimization Engineer will be a key player in Apple’s ongoing efforts to improve the efficiency of its cloud services. This role involves in-depth analysis of infrastructure usage patterns, and data‑driven capacity planning to ensure scalability and reliability while minimizing resource wastage.

Responsibilities

• You will help optimize the design, deployment, and operation of iCloud services.
• You will collaborate closely with engineering teams, data scientists, and finance experts to develop and implement strategies that align with Apple’s cloud sustainability and resource utilization principles.
• You will formulate and solve large‑scale optimization problems to allocate capacity, schedule workloads, and minimize cost under reliability and latency constraints.
• Your work will directly contribute to optimizing iCloud’s performance and resource utilization, influencing the unit cost of services and the overall customer experience.

Minimum Qualifications

• 3+ years of relevant experience in large‑scale cloud services or similar environments
• Strong software engineering background and experience with ML‑based modeling, time‑series forecasting, and data‑driven decision making for cloud services
• Exceptional analytical and problem‑solving skills, with the ability to communicate complex ideas clearly and effectively to cross‑functional teams
• Hands‑on experience with platform observability tools, enabling deep insights into service performance and helping to drive optimizations
• Experienced in developing cost models and strategies for software services, ensuring optimal resource utilization and cost‑effectiveness
• Bachelor or Master’s degree in Computer Science, Engineering, or a related field

Preferred Qualifications

• Experience applying classical optimization techniques to real‑world systems or infrastructure problems
• Demonstrable experience in capacity planning and resource optimization using machine learning and/or optimization techniques
• Knowledge of machine learning pipelines and service monitoring tools a plus
• Ph.D. in CS or related field with a focus on machine learning, optimization, or large‑scale distributed systems

Compensation and Benefits

Base pay for this role is determined by a range of $181,100 to $318,400 and 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. They are eligible for discretionary restricted stock unit awards and can purchase Apple stock at a discount under the Employee Stock Purchase Plan. Benefits include comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and reimbursement for certain educational expenses—including tuition. This role may also be eligible for discretionary bonuses, commission payments, and relocation.

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.

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