Machine Learning Engineer - Notifications & Personalization

Help build privacy-preserving machine learning that makes iOS notifications, widgets, and Focus prediction more intelligent, proactive, and personal.

Responsibilities

• Ship and evaluate machine learning solutions at scale
• Deploy ML models to millions of users and interpret real-world metrics to assess model and product impact
• Design, run, and iterate evaluation frameworks measuring model quality, user engagement, and product outcomes at scale
• Build instrumentation and telemetry pipelines to collect, analyze, and act on user signals across large populations
• Plan and implement experimentation for on-device ML models to evaluate deployed performance and optimize outcomes
• Implement, train, and optimize ML models using unsupervised and supervised learning techniques (classification, regression, and artificial neural networks) with Scikit-Learn and Apple frameworks such as CoreML and CreateML
• Apply reinforcement learning to personalize on-device suggestions, including recommendations for apps, people, and actions
• Deploy on-device inference using Python, Objective-C, and Swift, applying software engineering practices for clean, readable, testable, deployable code
• Select appropriate datasets and data representation methods, including identifying data sources and implementing algorithms to collect privacy-preserved data for model training
• Apply data preparation workflows including preprocessing, profiling, cleansing, validation, and transformation
• Use statistical and mathematical methods (for example, regression analysis) with Python and SQL-based querying tools to derive optimization insights from large datasets
• Apply strong product and design intuition to reason about how model decisions appear in the UI and influence user perception
• Collaborate closely with the Apple Design team to ensure intelligent features feel intentional, not intrusive
• Translate ambiguous user needs into measurable signals and tune models for user-perceived quality, not only statistical metrics
• Work within large-scale iOS operating system constraints such as performance, memory, and power
• Build across the full iOS system stack using Objective-C, Swift, and C++
• Deliver features spanning multiple system components, with familiarity in on-device inference constraints (latency, privacy, and resource budgets)
• Partner cross-functionally with teams including Privacy Engineering to enable privacy-preserved and secured data collection for training and optimization
• Develop UI-related capabilities through UI development, design, and prototyping experience

Requirements

• 7-10 years of experience
• Experience shipping and evaluating at scale
• Experience training and deploying machine learned models
• Experience building great user experiences
• Experience working on embedded operating systems
• BS, M.S., or PhD in Software Engineering, Computer Science, Machine Learning, or related field

Technologies

• Scikit-Learn
• CoreML
• CreateML
• Python
• Objective-C
• Swift
• SQL
• C++

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments and relocation (as applicable)
• Eligible for discretionary restricted stock unit awards
• Opportunity to purchase Apple stock at a discount through participation in Apple’s Employee Stock Purchase Plan

Pay & Benefits Notes

• Base pay range: $184,700 - $324,800 per year (depends on skills, qualifications, experience, and location)
• Eligibility for benefits, compensation, and stock programs depends on plan/program terms