In this role at Apple, you will be part of the Platform Architecture group, focusing on integrating hardware and software systems. You will collaborate with engineers to design and optimize machine learning applications on Apple silicon architecture. The position involves exploring ML workload mapping and developing performance models to inform architecture decisions. You will also evaluate ML model optimization techniques and provide insights to enhance workload efficiency on SoCs.

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

• Explore different ways of mapping ML workloads to Apple silicon.
• Develop performance models and simulations to inform architecture decisions.
• Critically evaluate ML model optimization techniques from literature.
• Propose new ideas based on insights gained from analysis.
• Provide guidance to software and algorithm teams on workload efficiency.
• Prototype algorithms on CPU/GPU/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.