The role is focused on exploring and optimizing machine learning workloads on Apple silicon within the Platform Architecture group. You will collaborate with engineers to drive the development of system-on-a-chip architecture and prototype systems. The team works at the intersection of machine learning applications and Apple silicon architecture, aiming to create highly optimized solutions. Your insights will guide software and algorithm teams in making workloads run efficiently on SoCs.

• Bachelor's degree in a relevant field.
• Experience in C/C++ and/or Python.
• Experience with hardware IPs such as ML hardware accelerators, GPU/CPU, or image/video processors.
• Experience with machine learning frameworks like PyTorch.
• MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 20+ years of relevant experience.
• Experience in optimizing and deploying machine learning models in production environments.
• Experience designing experiments to evaluate machine learning model optimization techniques.
• Understanding of compilers.

• Explore different ways of mapping machine learning workloads to Apple silicon.
• Develop performance models and simulations to inform architecture decisions.
• Critically evaluate machine learning model optimization techniques from literature.
• Propose new ideas based on insights gained from analysis.
• Provide guidance to software and algorithm teams on efficient workload execution.
• Prototype algorithms on CPU, GPU, or Neural Engine and analyze performance metrics.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.