Wireless Software & AI/ML Engineer Intern - Beijing

Apple is a place where extraordinary people gather to do their best work. Just be ready to dream big. The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that encourages the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Imagine what you could do here. At Apple, creative ideas have a way of becoming wonderful products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. Be a part of the Wireless Technologies and Ecosystems (WTE) team! The Wireless Software team is responsible for bringing groundbreaking cellular and wireless connectivity to Apple products including iPhone, iPad, Apple Watch, and Mac. In this role, you will explore the intersection of cellular communications and artificial intelligence, investigating how AI/ML models can analyze application traffic patterns and enable intelligent baseband optimizations to deliver seamless, world-class user experiences.

Student currently pursuing a Master’s or Ph.D. degree in Electrical Engineering, Computer Science, Telecommunications, Information Engineering, or related technical fields. Available for a full-time internship for at least 6 months based in Beijing. Good foundational knowledge of wireless communications or cellular network protocol stacks (LTE / 5G NR). Solid understanding of core machine learning / deep learning algorithms and experience with standard ML frameworks (e.g., PyTorch, TensorFlow, or Scikit-Learn). Excellent communication and collaboration skills, both verbally and written (in both Chinese and English). Familiarity with 5G NR protocol architecture and radio resource management concepts. Knowledge of multimedia streaming protocols and gaming QoS/QoE requirements. Experience with lightweight on-device ML model deployment or runtime optimization. Strong analytical, problem-solving, and debugging skills.