Senior Machine Learning Engineer, Analytics & Data Engineering

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.

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.

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.