As a performance engineer in Apple's Machine Learning Platform Technologies organization, you will address complex systems challenges related to scaling machine learning workloads across GPUs and TPUs. The focus will be on maximizing accelerator utilization and minimizing inefficiencies in large-scale ML training and inference. You will work closely with distributed systems and high-performance computing to enhance the infrastructure. This role requires strong software engineering skills and collaboration with cross-functional teams.

• Experience with large-scale distributed systems for AI/ML workloads running on GPUs or TPUs.
• Strong software engineering skills with experience developing and optimizing training frameworks using C/C++ or Python.
• Experience working on cross-functional projects with ML research and infrastructure teams.
• Familiarity with model architectures and various training techniques.
• Bachelor's degree in Computer Science or equivalent experience, with 7+ years of industry experience.

• Analyze accelerator performance and identify inefficiencies.
• Build solutions to maximize accelerator utilization and reduce idle capacity.
• Refine workload scheduling and orchestration across the compute fleet.
• Articulate high-level strategic metrics and underlying technical complexities.

• 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.