招聘
Benefits & Perks
•401(k) matching
•Flexible work arrangements
•Parental leave
•Professional development budget
•Generous paid time off and holidays
•Team events and activities
•Flexible Hours
•Parental Leave
•Learning
Required Skills
TypeScript
React
Node.js
About the Role
Join the Apple Service Engineering (ASE) team and drive innovation that matters! The ASE team builds and provides systems and infrastructure that fuel Apple's services. As part of this team, you will be responsible for building and integrating technologies that enhance people's lives. We are also tasked with enabling Apple Intelligence and Private Cloud Compute in the cloud. We are seeking a System Performance Engineer with a proven track record of developing technology that has made a significant impact.
Description
Collaborate cross-functionally with architecture, platform design, SOC architects, and software teams to deliver exceptional end-to-end performance that delights our customers. In this role, you'll be responsible for the performance of one or more products. Specifically, you'll be tasked with ensuring the end-to-end performance of Private Cloud Compute running Apple Intelligence in the cloud. This position demands technical expertise and depth to work on various elements of the stack, from SOC to the platform, software stack, and communication with the external world. You'll collaborate with architecture teams to define the product and set its performance targets, and with the SRE team to assess end-to-end performance and develop automation and infrastructure tools to evaluate the performance of our Apple Intelligence products. Strong problem-solving skills and effective communication are crucial for success in this role.
Minimum Qualifications
- 5+ years of experience as a Performance Engineer
- In-depth professional experience with cloud operations
- Experience with monitoring and observability tools such as Splunk, Grafana, and Prometheus
- Proven understanding of network technologies, protocols, and procedures for iOS and macOS
- Proven track record of working independently to own a complete functional area of an application or product
- Excellent communication & interpersonal skills
- Comfortable with troubleshooting/debugging/reproducing issues
- Scripting and programming skills in C/C++, Python, SQL, Shell
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field
Preferred Qualifications
- Experience with both traditional ML systems and GenAI LLMs
- Experience with data analytics platforms, such as Hadoop, Spark, or Snowflake
- Understanding of hardware components and hardware/software interaction
Equal Opportunity
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.
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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
M3
M4
M5
M6
L2 · Industrial Designer L2
0 reports
$320,450
total / year
Base
$128,180
Stock
$160,225
Bonus
$32,045
$224,315
$416,585
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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