About the role

What will you do at Apple?

At Apple, we're on the cutting edge of delivering transformative experiences

through Artificial Intelligence. If you're passionate about pushing the

boundaries of AI and hardware optimization, we want you to join our team! As a

Machine Learning System Software Engineer on the Apple Neural Engine (ANE) team,

you'll work to bring high-performance, low-power AI solutions to life on iconic

Apple products like the Vision Pro, iPhone, iPad, Mac, and more.

DESCRIPTION

This is a dynamic opportunity to work in a creative, collaborative environment

while developing groundbreaking technologies that will shape the future of

computing! We are looking for an engineer with deep expertise in system software

technology who is eager to tackle new challenges and responsibilities as the

role evolves. As the position progresses, there will be opportunities to

demonstrate technical leadership, influence key design decisions, collaborate

with and support other engineers, and help guide the direction of Apple's

AI-driven capabilities across the ecosystem. Are you ready to help us deliver

the next groundbreaking Apple products?

MINIMUM QUALIFICATIONS

BS and a minimum of 10 years relevant industry experience Experience defining

interfaces that are used by other teams or external developers, with attention

to lifecycle, error handling, and forward compatibility Deep proficiency in C

and C++ in large, production system software Understanding of runtime systems:

process/thread models, memory management, IPC/RPC, and resource lifecycle

Understanding of software-hardware interfaces: registers, DMA, command queues,

or similar accelerator interaction patterns Experience shipping production

system software

PREFERRED QUALIFICATIONS

Experience building or extending ML runtimes, inference engines, or accelerator

driver stacks (e.g., TensorRT, ONNX Runtime, XLA, Metal, Vulkan compute, or

similar) Familiarity with Swift/Rust or another memory-safe systems language

Familiarity with ML model compilation pipelines and how runtime APIs interact

with compiler outputs (graph IR, compiled binaries) Experience with multi-client

runtime scenarios: arbitrating hardware access, managing priority/QoS, and

handling client lifecycle (ex: connect, disconnect, crash recovery) Knowledge of

neural network inference: operator execution, tensor memory layout, pipelining,

and batching strategies Strong communication skills and experience working

across team boundaries (framework teams, compiler teams, hardware teams)

Which skills does this role require?

CC++System SoftwareMachine LearningNeural EngineHardware OptimizationRuntime SystemsMemory ManagementIPC/RPCAccelerator Driver StacksCompiler PipelinesTechnical LeadershipApple Neural EngineIPCRPCDMASoftware-Hardware InterfacesProduction SoftwareArtificial IntelligenceComputingEcosystem

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