Machine Learning Architect, Platform Architecture

Apple • Cupertino, CA

2d

About The Position

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. 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.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• Explore different ways of mapping ML workloads to Apple silicon
• Develop performance models/simulations
• Inform and validate architecture decisions
• Critically evaluate ML model optimization techniques from the literature, analyzing what works and why, and proposing new ideas
• Gain insights on how to make workloads run efficiently on our SoCs
• Provide guidance to software and algorithm teams

What This Job Offers

• Job Type: Full-time
• Career Level: Senior