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ML Engineering Manager - iCloud-ASE

Apple

ML Engineering Manager - iCloud-ASE

Apple

Cupertino, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$198,300 - $342,800

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

Apple

Public

A 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