Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Machine learning
Time-series forecasting
Software engineering
Data analysis
Optimization
In Apple's i Cloud 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 i Cloud'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 i Cloud 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 i Cloud's performance and resource utilization, influencing the unit cost of services and the overall customer experience.
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
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
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. Learn more about your EEO rights as an applicant .
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 $181,100 and $318,400, 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.
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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