Machine Learning Architect, Platform Architecture

Role Number: 200685275-0836

Summary

At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how our technologies work in unison, drive development of our renowned system-on-a-chip architecture and forward-looking prototype systems. Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture, system, software, and algorithm teams to develop integrated, highly optimized solutions for machine learning applications.

Description

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

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.