Internship - Machine Learning And ai - Foundation Model Infrastructure H/F apple

Application Deadline - 5th December 2025 Are you interested in solving challenging technical problems and contributing to systems that support large-scale machine learning models? The ML Infrastructure team, part of the Machine Learning Platform Technologies organization at Apple, builds frameworks, services, and tools that power Apple's foundation models on servers. Our infrastructure supports a wide range of Apple products and services, including Search, Music, TV, App Store, Messages, Photos, Safari, Siri, and more. It handles millions of requests each day with a focus on efficiency, scalability, and reliability. You will have the opportunity to work on technologies that make large language, vision, and speech models more efficient and deployable at scale. You'll collaborate with experienced engineers, learn about modern ML infrastructure, and help improve the systems that bring intelligent features to Apple products used by people around the world. As an intern on this team, you will: - Collaborate with engineers to analyze and optimize inference performance for language, vision, and multimodal models. - Develop tools and utilities that help understand bottlenecks across hardware platforms and workloads. - Contribute to the design and evaluation of new techniques for efficient model serving and deployment. - Learn about distributed systems, GPU computing, and large-scale ML workflows in a production environment. - Work in an environment that values creativity, curiosity, and collaboration. This internship will provide hands-on experience with the infrastructure behind Apple's AI technologies and offer insight into how research ideas are transformed into scalable, reliable systems.
- Currently a pursuing a degree in Computer Science, Machine Learning, or a related field as a final year Bachelor's Student or a Master's Student.
- Solid understanding of ML fundamentals, data structures, and algorithms.
- Proficiency in Python and good coding practices.
- Strong collaboration, curiosity, and problem-solving skills.

- Experience with PyTorch or TensorFlow.
- Familiarity with Transformer models or large-scale ML architectures.
- Exposure to GPU programming, Docker, Kubernetes, or cloud environments.
- Interest in distributed systems, inference optimization, or ML deployment.

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.