Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Machine Learning
Team Leadership
Anti-abuse Systems
Classification Models
At Apple, we believe that breakthrough products emerge when engineering quality meets visionary thinking. We're seeking a Machine Learning Engineering Manager to own the anti-spam solutions for i Cloud Mail, Calendar, and Contacts-someone who will be an influential force in ensuring millions of i Cloud customers have a great experience by preventing spam from entering users' mailboxes and calendars.
You will manage a team of engineers and be responsible for all overall anti-abuse solutions, integration into Mail, Calendar and Contacts systems, and the end-to-end user experience of reporting spam.
You will also be collaborating with various teams like Apple Trust and Safety, Anti-abuse Operations team, and other key stakeholders to ensure seamless experiences for i Cloud customers.
Description:
As the Engineering Manager for i Cloud Anti-Abuse, you will lead a critical team responsible for protecting millions of i Cloud users from spam, phishing, and other malicious content across Mail, Calendar, and Contacts. This role combines deep technical expertise in machine learning and anti-abuse systems with strong leadership skills to drive innovation in user protection. This role offers the opportunity to make a significant impact on user safety and experience while working with cutting-edge technology at one of the world's most innovative companies
Preferred Qualifications:
Comprehensive understanding of various abuse vectors and techniques to overcome them
Demonstrated expertise in machine learning and various classification model techniques, reputation systems, and applying these techniques toward preventing abuse
Proven expertise in end-to-end machine learning lifecycle including data collection, processing, training, model building, inference, and feedback loops
Highly collaborative with excellent communication skills and the ability to work with various key stakeholders, present to executives, and lead partner teams toward common goals
Ability to balance and prioritize strategic long-term investments in anti-abuse while effectively handling daily customer complaints and executive escalations
Strong understanding of protocols like IMAP, SMTP, CalDAV, and CardDAV
Experience in email security, content filtering, or related security domains
Experience working with systems serving millions of users
Understanding of privacy-preserving machine learning techniques and data handling best practices
Minimum Qualifications:
Manage and mentor a team of talented engineers specializing in anti-abuse technologies and machine learning systems
Define and execute the technical roadmap for anti-abuse solutions across i Cloud Mail, Calendar and Contacts
Partner with Apple Trust and Safety, Anti-abuse Operations, and other key stakeholders to deliver comprehensive protection solutions
Oversee the integration of anti-abuse solutions into Mail, Calendar, Contacts pipelines and ensure optimal performance and user experience
Lead response to daily customer complaints and executive escalations while maintaining strategic long-term focus
Drive advancement in machine learning techniques for abuse detection and prevention
Ensure that anti-abuse measures maintain the seamless, intuitive experience Apple customers expect
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 $198,300 and $342,800, 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
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total / year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
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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