Senior Machine Learning Engineer, Analytics & Data Engineering

Summary

The Apple Services Engineering team combines art and technology to power some of Apple's most beloved services—including the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. We build secure, performant, and privacy-first solutions on a massive global scale, delivering rich entertainment in over 35 languages to more than 150 countries.
We are seeking an extraordinary Machine Learning Engineer to join our geographically diverse team. In this role, you will innovate, design, and craft the AI/ML foundation that keeps our AI/ML solutions secure, private, performant, and highly scalable. If you are passionate about improving engineering processes, exploring cutting-edge tech, and building robust systems at Apple-scale, we want to hear from you!

Description

As a Machine Learning Engineer on our team, you will dive into a variety of unique problems that directly impact Apple Products.
* Build & Innovate: Research and develop state-of-the-art AI/ML solutions and tools that transform how we train, deploy, and monitor models that power features in Apple Products.
* Scale & Secure: Work at the intersection of scale and privacy. You will design secure, private, and highly performant systems, ensuring our systems respect and protect user privacy as a core engineering feature.
* Collaborate & Influence: Act as a technical leader. You will collaborate with broader teams across Apple, actively participating in design discussions, giving and receiving constructive feedback, and mentoring junior engineers.
* Champion Quality: Participate in our highly collaborative environment to elevate our engineering standards. From design reviews and rigorous code reviews to robust test automation, you will ensure our AI/ML systems are maintainable and resilient.

Preferred Qualifications

AI/ML Infrastructure & Ops: Experience developing and maintaining large-scale ML infrastructure (services, pipelines, frameworks, and deployment tooling like Ray, Kubernetes, MLflow) is a plus
AI-Assisted Engineering: Proven proficiency in leveraging advanced Generative AI and LLM assistants (e.g., Claude, Gemini, etc) as force-multipliers across the software development lifecycle with high quality always in mind.
Soft Skills & Autonomy: Strong communication skills for requirement clarifications and cross-functional collaboration. Ability to lead with a high level of autonomy, driving critical initiatives from concept to production.

Minimum Qualifications

PhD or Master’s degree in Machine Learning, Computer Science, Computer Engineering, or equivalent practical experience.
Core Experience: 5 - 7+ years of professional software engineering experience with a strong focus on AI/ML engineering.
Engineering Foundations: Robust engineering design skills with expert proficiency in Python and/or Java/Scala. Deep understanding of computer science fundamentals like data structures, algorithms, and system design.
AI/ML Foundations: Solid understanding of traditional machine learning algorithms (supervised, unsupervised, semi-supervised) and cutting edge genAI technologies. Hands-on experience with modern AI/ML frameworks (e.g., PyTorch, TensorFlow, JAX).
Distributed Systems & Big Data: Proven experience with large-scale distributed data processing technologies such as Ray, Spark, or modern alternatives.