Machine Learning System Software Engineer

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Machine Learning System Software Engineer in USA new

Apple
Full time
Email

USA
11/09/2026
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Sunnyvale, CA

Responsibilities

Develop and ship production system software for the Apple Neural Engine and AI capabilities across Apple products.
Define interfaces for other teams and external developers, including lifecycle, error handling, and forward compatibility considerations.
Build or extend ML runtimes, inference engines, or accelerator driver stacks.
Work with runtime systems, software-hardware interfaces, process and thread models, memory management, and resource lifecycles.
Support multi-client runtime scenarios such as hardware arbitration, priority and QoS management, client lifecycle handling, and crash recovery.
Collaborate across framework, compiler, and hardware teams and contribute to technical design direction.

Requirements

Bachelor of Science degree and a minimum of 3 years of relevant industry experience.
Deep proficiency in C and C++ for large, production system software.
Experience defining interfaces used by other teams or external developers.
Experience shipping production system software.
Understanding of process and thread models, memory management, IPC/RPC, and resource lifecycle.
Understanding of software-hardware interfaces such as registers, DMA, and command queues.
Preferred experience with TensorRT, ONNX Runtime, XLA, Metal, Vulkan compute, or similar technologies.
Preferred familiarity with Swift, Rust, or another memory-safe systems language.
Preferred familiarity with ML model compilation pipelines, graph IR, compiled binaries, and runtime APIs.
Preferred knowledge of neural network inference, operator execution, tensor memory layout, pipelining, and batching strategies.
Strong communication skills and experience working across team boundaries.

Apple

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. And the same innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it. This i...

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