We will be hiring for the below internship in 2025/2026 and across the available start dates: Winter 2025 or Spring / Summer 2026. Are you ready to be at the forefront of architecting the next generation of Apple GPUs? This role will require you to analyze the performance of existing and future looking workloads and propose, alongside with world-class GPU and SoC Architects, new features and research on novel ideas to boost to new heights the performance of our GPUs. To do so, you’ll use performance and energy models to evaluate, iterate and tune the different ideas until the proposal is mature enough to be presented to senior GPU Architects to decide on its feasibility. You’ll also cross-collaborate as a larger architecture and performance team to maintain and improve the simulation environment and look for ways to boost the productivity of the entire team. Currently pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, Computer Engineering, Electrical and Computer Engineering, or a related field. At the end of the internship, you must return to school to continue your education or the internship must be the last requirement for you to graduate. Strong coding skills including object-oriented programming with C and C++ Knowledge of scripting languages such as Perl, Python or Ruby Strong understanding of common data structures, algorithms, and design patterns A curiosity about GPU / CPU / SOC architecture and micro-architecture Strong interpersonal and analytical skills, with an ability to make data driven decisions Ability to work well within a team and be productive under tight schedules Knowledge of performance modelling, logic design and power Curiosity about machine learning and classification algorithm Experience optimising rendering/parallel compute algorithms, drivers and/or compilers for one or more GPU architectures Prior experience on hardware architectural modelling and hardware description languages Experience with one or more GPU APIs (Metal, DX12, Vulcan, CUDA, OpenGL, OpenCL) Knowledge of performance simulation environments