Job Description

Apple's ML Frameworks team is seeking engineers with a strong systems background to work on high-performance, distributed inference of GenAI applications on custom-built server hardware. The role involves optimizing machine learning libraries for Apple Silicon and influencing the design of next-generation GPU architectures.

Requirements

3+ years of programming and problem-solving experience with C/C++/ObjC
Experience with GPU kernel development & optimizations using compute programming models such as Metal, CUDA etc.
Experience with system level programming and computer architecture
Experience with Distributed training or inference techniques

Responsibilities

Work on cutting-edge ML inference framework project and optimize code for efficient and scalable ML inference using distributed compute strategies such as data, tensor, pipeline and expert parallelism.
Develop kernel and compiler level optimizations and perform in-depth analysis to ensure the best possible performance across Server hardware families.
Apply advanced model optimization techniques including speculation, quantization, compression, and others to maximize throughput and minimize latency.
Collaborate closely with hardware, compiler, and systems teams to align software performance with hardware capabilities.
Analyze and improve performance metrics such as end-to-end latency, TTFT, TBOT, memory footprint, and compute efficiency.
Implement features of Metal device backend for ML training acceleration technologies

Benefits

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.