Senior Machine Learning Engineer, Apple Services Engineering AI/ML

The Apple Services Engineering AI/ML organization is looking for a Machine Learning Engineer to help build next-generation media discovery experiences for Apple's ground breaking devices and platforms, leveraging Artificial Intelligence & Machine Learning at scale. Wonder how Apple's Media Products show relevant and rich Discovery experiences covering search, browse and recommendations for Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design and develop AI/ML driven Discovery features for billions of Apple users worldwide! Propose, prototype and evaluate algorithm improvements that power these rich experiences. Evangelize and build reusable AI capabilities to enhance the foundation of how these user facing features are built in the larger organization. The Apple Services Engineering (ASE) organization is one of the most exciting examples of Apple's long-held passion for combining art with technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. 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 40 languages to more than 170 countries. Our scientists and engineers build secure, end-to-end solutions powered by Artifical Intelligence & Machine Learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers in ASE 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 You will drive technical advancement, influence product direction, and be part of a team responsible for bringing the latest advancements in Machine Learning, Natural Language Processing and Generative AI to drive major impact on how users discover Apple Media content on devices worldwide! This is a team with strong expertise in Information Retrieval, Machine Learning, Language Modeling, Generative AI, Data Mining, and Distributed Computing (Hadoop, Scala, Spark). You will use data driven analysis to ideate, evaluate and prioritize features, and conduct A/B Tests to ensure we objectively measure improvements. You will ensure successful delivery of features, code, data, and models to production. You will collaborate with researchers, engineers, and operations teams to ensure that features and models are functioning at or above expected performance levels, globally in languages from Arabic to Vietnamese and everything in between! Key Responsibilities: * Inference Service Development: Design, develop, and deploy high-performance machine learning inference services with a focus on scalability and efficiency. * Big Data Pipeline Engineering: Build and maintain data processing pipelines to support model training and tuning across large datasets. * Model Training Pipeline Optimization: Manage and optimize GenAI & Machine Learning training pipelines to improve performance in distributed computing environments. * Areas of focus: Work on implementation of applications such as summarization, question answering, chatbots, information retrieval, semantic search, and text generation.

Minimum Qualifications

• BS in Computer Science, Computer Engineering, Information Systems, Electronic Engineering or related fields.
• 4+ years of experience working in the AI/ML field.
• Strong programming skills in Java, Scala, Python and experience with ML libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, or similar.
• Solid understanding of modern ML architectures, big data pipelines, and evaluation techniques.

Preferred Qualifications

• MS/PhD in Computer Science, Computer Engineering, Information Systems, Electronic Engineering or related fields.
• 2+ years of experience working in the AI/ML field.
• Expertise in large-volume big data processing (batch or streaming) and experience with Apache Spark and Apache Flink .
• Familiarity with agentic workflows, Retrieval-Augmented Generation (RAG), vector databases (e.g., FAISS, Pinecone), and knowledge graphs.
• Strong communication skills and adept at working with cross functional partners to design cohesive engineering solutions that scale ML products for billions of users.

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 $147,400 and $272,100, 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.

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 .