Across Apple Services Engineering (ASE), 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 cost models across ASE’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
Manager, ASE Efficiency 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. You will connect application and business demand to infrastructure requirements, then use measured utilization to improve forecasting and optimization decisions.
Minimum qualifications
7+ years of relevant experience in large-scale cloud services or similar environments
2+ years of engineering management experience
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’s 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
PhD in CS or related field with a focus on machine learning, optimization, or large-scale distributed systems
Pay & benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $225,600 and $338,400, and your base pay 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. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.