Senior Machine Learning Engineer, Analytics & Data Engineering

About the role

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.

Responsibilities

• 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. 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. Collaborate with broader teams across Apple, actively participate in design discussions, give and receive constructive feedback, and mentor 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, ensure our AI/ML systems are maintainable and resilient.

Minimum qualifications

• Education: 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).
• 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.