Machine Learning Architect, 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 critically evaluate ML model optimization techniques from the literature, analyzing what works and why, and proposing new ideas that build on what you learn. You will gain insights on how to make workloads run efficiently on our SoCs and provide guidance to software and algorithm teams. Minimum Qualifications Bachelor’s degree Experience in C/C++ and/or Python Experience in hardware IPs: ML HW accelerators, GPU/CPU, image/video processors or similar. Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms Preferred Qualifications MS or PhD in EE/CE/CS or related field 20+ years of relevant experience Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments Experience designing experiments to evaluate ML model optimization techniques Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models Verbal and written communication skills for collaborating with partner teams Understanding of compilers