Machine Learning System Software Engineer

Apple Inc

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Sunnyvale, CA
Salary: $184,700–$324,800 / yr
Posted: 75 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k

This role $255k

$155k $343k

below market most similar roles pay here above market

This role pays more than 85% of similar roles. Most pay $192,050–$249,000 — the blue band above. At the midpoint, this role pays about $255k versus about $221k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Machine Learning System Software Engineer

Role Posting Log in to save

The Machine Learning System Software Engineer joins the Apple Neural Engine team to develop high-performance, low-power AI solutions for products like the Vision Pro and iPhone. The role involves designing and implementing APIs for the Neural Engine, specifically defining how clients load, compile, schedule, and execute models on device. Key responsibilities include architecting APIs for memory allocation, multi-model scheduling, and concurrent execution while co-designing the runtime-to-silicon interface with driver and firmware teams. The engineer will profile and optimize end-to-end inference paths to identify bottlenecks. Required skills include deep proficiency in C and C++, knowledge of runtime systems like IPC and memory management, and experience with software-hardware interfaces such as DMA and registers. Preferred experience includes ML runtimes, Swift, Rust, and neural network inference strategies.

Skills

C C++ Swift Rust TensorRT ONNX Runtime XLA Metal Vulkan ML Runtime Inference Engines Graph IR IPC RPC DMA Memory Management Multi-model Scheduling Neural Network Inference

What you'll do

Design and implement APIs for the Neural Engine to manage model loading, compilation, scheduling, and execution.
Architect APIs for model lifecycle management, memory allocation strategies, and multi-model concurrent execution.
Co-design the runtime-to-silicon interface with driver, firmware, and compiler teams to expose new hardware features.
Profile and optimize end-to-end inference paths to identify bottlenecks in scheduling and compilation.
Support clients in adopting APIs and ensuring efficient integration into their workflows.
Manage multi-client runtime scenarios including hardware access arbitration, priority/QoS, and crash recovery.

What we're looking for

BS degree and a minimum of 10 years of relevant industry experience.
Deep proficiency in C and C++ in large, production system software.
Experience shipping production system software.
Experience defining interfaces used by other teams or external developers with attention to lifecycle and error handling.
Understanding of runtime systems including process/thread models, memory management, IPC/RPC, and resource lifecycle.
Understanding of software-hardware interfaces such as registers, DMA, and command queues.
Experience building or extending ML runtimes, inference engines, or accelerator driver stacks (preferred).
Familiarity with Swift/Rust, ML model compilation pipelines, or neural network inference (preferred).

Save