Machine Learning Engineer, Platform Architecture

In this role, you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will gain insights on how to make workloads run efficiently on our SoCs and communicate what we learn to software and algorithm teams. Minimum Qualifications Bachelor’s degree Ability to program in C/C++ and/or Python Knowledge of computer architecture fundamentals Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar Preferred Qualifications MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments Experience in creating SoC or IP performance models/simulations Verbal and written communication skills for collaborating with partner teams Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models Understanding of compiler frameworks/technologies