Machine Learning Systems Engineer

As part of Apple Cloud Platform, our team is responsible for building libraries and services which form the foundations of critically important systems at Apple.

Specifically, as a ML Systems Engineer, you will focus on building software stack to run large machine learning models (generative AI, LLMs) over multiple high performance Apple Silicon SoCs.

Key Qualifications

• Practical experience running and evaluating machine learning models for quality and performance metrics
• Experience in system-level code optimisation and power/performance evaluation for ML acceleration hardware
• Large‑scale server side development experience
• Experience programming in Swift, C, C++, iOS/macOS, XCode
• Bonus qualification: familiar with Apple ML stack (ANE, CoreML, MPS/Metal), high‑level general distributed ML stack (PyTorch‑distributed, NCCL) and high throughput inter‑chip communication systems.

Responsibilities and Work

We write software in Swift and C++ to build services and infrastructure around innovative generative AI and machine learning. We write performant and scalable frameworks to distribute and coordinate ML inference tasks to different hardware acceleration IP blocks on different SoCs; we build jobs to deploy and load models, and support high level machine learning platforms. Our software has a growing user base and the team is looking to expand to build amazing products making it a truly exciting place to work.

Education & Experience

B.S. in Computer Science or other numerate subject, with 6+ years experience; or M.S. in Computer Science or other numerate subject, with 4+ years experience

Additional Requirements

Quality focus - produce reliable, maintainable, deliverable software

Comfortable diving deep - working across multiple levels of abstraction

Good at handling relationships & communication - collaborate well with colleagues across a wide range of functions.