The posting
Summary
Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy recommendation models that personalize the App Store for billions of users worldwide! See your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Games and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.
Our researchers and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
Description
We are looking for an exceptional Machine Learning Engineer to help us design, build, and ship recommendation models that power personalization across the App Store. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
Responsibilities
Design, train, and launch recommendation models that improve relevance and business metrics on key App Store surfaces. Own ranker modules end-to-end: candidate representation, feature engineering, model architecture, offline evaluation, A/B experimentation, and production monitoring. Drive adoption of state-of-the-art ranking techniques from research prototypes into production. Partner closely with ML researchers, data engineers, and infrastructure teams to productionize new modeling approaches with high reliability and low latency. Ship production-quality code and drive engineering best practices, system architecture, and code quality within the team. Help chart the future growth of personalization across Apple's services ecosystem.
Minimum Qualifications
Bachelor's and Master's in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc. 3+ years of relevant work experience. Hands-on experience with production-level recommender systems. Deep knowledge of recommendation systems, design patterns and tools, with particular depth in deep-learning architectures and multi-task modeling. Proven track record of shipping recommendation models to production at scale, with a strong understanding of the constraints of serving billions of users. Knowledge of modern recommendation architectures across retrieval and ranking, multi-task learning, sequence and transformer-based models, generative recommenders, and multi-objective optimization. Proven grasp of the open-source Python ML/AI tech stack, including TensorFlow, PyTorch, scikit-learn, numpy-scipy-pandas. Familiarity with big data technologies and distributed computing (e.g., Spark, Hadoop, Kafka). Familiarity with using LLM-powered tools (coding and research assistants) to accelerate day-to-day engineering and research workflows. Strong written & oral communication skills.
Preferred Qualifications
PhD in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
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 $142,300 and $263,300, 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.
EEO Statement
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
Accessibility
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Application Deadline
Apple accepts applications to this posting on an ongoing basis.
