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Senior Machine Learning Engineer, Privacy-Preserving Personalization

Apple

Senior Machine Learning Engineer, Privacy-Preserving Personalization

Apple

Seattle, WA

·

On-site

·

Full-time

·

2w ago

Compensation

$171,600 - $302,200

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Healthcare

401k

Equity

Learning

Required Skills

Machine Learning

Big Data

Data Architecture

Distributed Systems

Software Engineering

Imagine shaping how millions of people discover content they love on the App Store, Apple Music, and Apple TV+. Our team is responsible for the intelligence that powers these deeply personal experiences.
We are at a pivotal moment, defining the next generation of personalization in the era of Generative AI. Our challenge is unique and profound: how do we deliver state-of-the-art, magical user experiences while upholding our unwavering commitment to user privacy?

Description:

This is not a standard ML role. We are looking for a pioneering engineer to help us invent the future. You will be a foundational member of the team architecting how we manage and learn from data, setting the standard for privacy and compliance across the globe.

","responsibilities":"Architect Petabyte-Scale Systems: Design, build, and optimize robust data processing pipelines that handle petabytes of data efficiently, reliably, and with privacy at their core.

Pioneer Privacy-Preserving AI: Research, prototype, and deploy innovative solutions for privacy in a Gen-AI world. This includes thinking through everything from on-device intelligence to novel data anonymization and compliance verification techniques.

Build Intelligent Agents: Design and develop frameworks for agentic AI systems, ensuring they can operate effectively and autonomously within strict privacy and compliance boundaries.

Define Data Strategy: Go beyond implementation to think strategically about our data ecosystem. You will lead efforts in defining data ontology, ensuring data portability, and embedding world-class data security principles into every system we build.

Navigate Global Compliance: Collaborate closely with legal, policy, and product teams to translate complex global regulations (like GDPR, CCPA, and others) into concrete engineering solutions, ensuring our systems are compliant by design.

Innovate and Influence: Act as a thought leader within the organization, driving the technical vision for how we balance personalization and privacy in our most important products.

Preferred Qualifications:

Familiarity with building or integrating agentic systems and Large Language Models (LLMs).

Privacy & Compliance Expertise: Deep experience and passion for privacy-preserving techniques (e.g., Differential Privacy, Federated Learning, k-Anonymity) and their practical application.

Experience with MLOps best practices for model deployment, monitoring, and governance in a regulated environment.

A strong background in software engineering, with proficiency in languages like Python, Scala, or Java.

Minimum Qualifications:

BS or MS in Computer Science, Statistics, or a related field, preferably with a focus on machine learning or data privacy.

Senior-Level Experience: A proven track record of shipping complex, large-scale machine learning systems to production.

Mastery of Big Data: Expertise in designing and building distributed data processing systems at petabyte scale using technologies like Spark, Flink, Beam, or similar frameworks.

Strategic Data Mindset: Demonstrated experience thinking critically about data architecture, including data ontology, data security models, and data portability challenges.

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 $171,600 and $302,200, 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