Machine Learning System Software Engineer (m/f/d)

Summary

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?

Responsibilities

• Design and implement API's for Apple's Neural Engine - defining how clients load, compile, schedule and execute models on device
• Architect APIs which provide client control of model lifecycle management, memory allocation strategies, multi-model scheduling, and concurrent execution — ensuring the runtime scales with new hardware capabilities
• Collaborate deeply with driver, firmware and compiler teams to co-design the runtime-to-silicon interface, ensuring new hardware features are exposed with correct abstractions
• Profile and optimize end-to-end inference paths, identifying bottlenecks in scheduling, compilation, and inference execution
• Support clients in adopting APIs and ensuring efficient integration

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)

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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