Senior Machine Learning Engineer, Analytics & Data Engineering

The Apple Services Engineering team combines art and technology to power some of Apples most beloved servicesincluding 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 are seeking an extraordinary Machine Learning Engineer to join our geographically diverse 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!

As a Machine Learning Engineer on our team you will dive into a variety of unique problems that directly impact Apple Products.n* Build u0026 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.n* Scale u0026 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.n* Collaborate u0026 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.n* 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.

PhD or Masters degree in Machine Learning Computer Science Computer Engineering or equivalent practical Experience: 5 - 7 years of professional software engineering experience with a strong focus on AI/ML 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 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).nDistributed Systems u0026 Big Data: Proven experience with large-scale distributed data processing technologies such as Ray Spark or modern alternatives.

AI/ML Infrastructure u0026 Ops: Experience developing and maintaining large-scale ML infrastructure (services pipelines frameworks and deployment tooling like Ray Kubernetes MLflow) is a plusnAI-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 Skills u0026 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.