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Machine Learning Engineer, On-Device ML - Apple Ads Cupertino, California, United States Machine Learning and AI Add to Favorites Machine Learning Engineer, On-Device ML - Apple Ads 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. 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.

The following information provides an overview of the skills, qualities, and qualifications needed for this role.

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. 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 . Add to Favorites Machine Learning Engineer, On-Device ML - Apple Ads

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