Machine Learning Engineer, On-Device ML - Apple Ads

Apple; Cupertino (CA); On-site; USD 143,000 - 265,000; Full time

Job summary

Join a forward-thinking company as a Machine Learning Engineer focusing on on-device ML for Ads. You'll lead innovative projects that enhance user experiences while ensuring privacy. This role involves designing and optimizing machine learning models, implementing cutting-edge techniques, and collaborating with a dynamic team. With a commitment to innovation and excellence, this opportunity offers a chance to make a significant impact in the tech industry. If you're passionate about machine learning and eager to drive change, this is the perfect role for you.

Benefits

Comprehensive medical and dental coverage

Retirement benefits

Employee stock purchase plan

Discounted products and free services

Educational reimbursement

Qualifications

• 3+ years in ML engineering focusing on mobile/on-device ML.
• Strong proficiency in Swift, Objective-C, and Python.

Responsibilities

• Design and optimize on-device ML models for user preferences.
• Implement and fine-tune deep learning models for efficiency.

Skills

Machine Learning Engineering

On-Device Machine Learning

Swift

Objective-C

Python

Core ML

TensorFlow Lite

Private Federated Learning

Differential Privacy

Education

Bachelor's Degree in Computer Science or related field

Master's Degree in Machine Learning or AI

Tools

Core ML

Metal

Xcode

TensorFlow Lite

PyTorch Mobile

Job description

Machine Learning Engineer, On-Device ML - Apple Ads

**Cupertino, California, United States**

**Machine Learning and AI**

**Summary**

Posted: **May 05, 2025**

Weekly Hours: **40**

Role Number: **200601298**

At Apple, we strive every day to create products that enrich people’s lives. Our Advertising Platforms group enables users worldwide to discover new content seamlessly while empowering publishers and developers to promote and monetize their work. Our technology powers advertising in the App Store and Apple News, delivering highly-performant, privacy-first solutions that set new industry standards.

We're seeking an adventurous and strategic leader to drive innovation in Ads Signals Intelligence! This role requires a deep understanding of Ad network behavior and the ability to develop and prioritize an innovation roadmap that spans multiple technical domains. You'll lead a team that designs, develops, and delivers innovative capabilities, differentiating Apple’s Ad Platforms and driving key business outcomes.

**Description**

- Design, develop, and optimize on-device machine learning models for learning user preferences within the App Store ecosystem.

- Implement, benchmark, and fine-tune deep learning models for efficiency, latency, and power consumption on iOS devices.

- Work with Core ML, Metal, and other Apple ML frameworks to deploy models efficiently and securely.

- Ensure all ML computations remain on-device, preserving user privacy while maintaining model effectiveness.

- Develop and apply Private Federated Learning and Differential Privacy techniques to ensure user data never leaves the device while enabling personalized experiences.

- Optimize models for various iOS devices, ensuring performance across different generations and hardware capabilities.

- Develop tools and techniques for model compression, quantization, pruning, and hardware acceleration to enable real-time inference.

- Stay updated with the latest developments in privacy-preserving AI, on-device learning, and Apple ML advancements.

**Minimum Qualifications**

+ 3+ years in ML engineering with a focus on on-device/mobile ML, preferably iOS.

+ Strong proficiency in Swift, Objective-C, and Python.

+ Experience with Core ML, Metal, TensorFlow Lite, PyTorch Mobile, or similar frameworks.

+ Knowledge of model quantization, pruning, knowledge distillation, and hardware acceleration (e.g., Neural Engine, GPU optimizations).

+ Familiarity with iOS development tools, Xcode, and app deployment processes.

+ Experience or familiarity with Private Federated Learning and Differential Privacy is a strong plus.

+ On-Device Personalization: Experience with learning user preferences without data leaving the device is highly desirable.

+ Ability to troubleshoot and debug performance bottlenecks in ML models and iOS applications.

**Preferred Qualifications**

+ Hands-on experience with Private Federated Learning and Differential Privacy.

+ Experience with Apple Neural Engine optimizations.

+ Background in embedded systems or edge computing.

+ Knowledge of real-time inference in resource-constrained environments.

+ Experience building personalization models that adapt on-device without cloud interaction.

**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 $143,100 and $264,200, 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. (https://www.apple.com/careers/us/benefits.html)

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.