Machine Learning System Software Engineer

Responsibilities

You will develop high-performance, low-power AI solutions for Apple products by working on the Apple Neural Engine team. The role involves technical leadership, influencing design decisions, and collaborating across teams to shape the future of AI-driven computing.

Requirements

Candidates must have a Bachelor's degree and at least 3 years of industry experience with deep proficiency in C and C++. Strong knowledge of system software, runtime environments, and software-hardware interfaces is required.

Skills

• C
• C++
• System Software
• Machine Learning
• Neural Network Inference
• Runtime Systems
• Memory Management
• IPC/RPC
• Hardware-Software Interfaces
• DMA
• Command Queues
• Inference Engines
• Compiler Pipelines
• TensorRT
• Metal
• Vulkan

About this role

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 3 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)

About Apple

Computers and Electronics Manufacturing · 10,001+ employees · headquartered in Cupertino, California · founded 1976