> Markdown version of [/jobs/ext/153755-machine-learning-engineer-platform-architecture](https://www.wearedevelopers.com/jobs/ext/153755-machine-learning-engineer-platform-architecture). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer, Platform Architecture

- **Company:** Apple Inc.
- **Location:** Cupertino, CA, United States
- **Experience:** Experienced
- **Salary:** $147,400.0 - $272,100.0
- **Contract:** Permanent contract
- **Skills:** Computing Platforms, C++ (Programming Language), Microprocessors, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Systems Architecture, Pytorch, Machine Learning Operations
- **Published:** May 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a60f81e4eabd8a55

## About the Role

Do you have experience in System performance optimization?, Do you have a Bachelor's degree?, MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience

Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms

Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments

Experience in creating SoC or IP performance models/simulations

Verbal and written communication skills for collaborating with partner teams

Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models

Understanding of compiler frameworks/technologies

Minimum Qualifications

Bachelor's degree

Ability to program in C/C++ and/or Python

Knowledge of computer architecture fundamentals

Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar

## Description

In this role, you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will gain insights on how to make workloads run efficiently on our SoCs and communicate what we learn to software and algorithm teams.","responsibilities":"Create optimized implementations of ML workloads on Apple silicon including Neural Engine, GPU, and CPU.

Collaborate with IP and SoC architecture teams to develop performance models and simulations of future hardware.

Conduct performance studies to inform and validate architecture decisions.

Collaborate with system teams to create high-level performance models of emerging ML techniques and analyze system architecture trade-offs.


## Related Videos

- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [On developing smartphones on wheels](https://www.wearedevelopers.com/videos/258-on-developing-smartphones-on-wheels)
- [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs)
- [Edge AI on iOS: Beyond the Cloud, Designing the Next Generation of Intelligent On-Device Apps](https://www.wearedevelopers.com/videos/100225-edge-ai-on-ios-beyond-the-cloud-designing-the-next-generation-of-intelligent-on-device-apps)
- [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning)
- [From Model to Metal: An Open Source Stack for Accelerating Intelligence](https://www.wearedevelopers.com/videos/1636-from-model-to-metal-an-open-source-stack-for-accelerating-intelligence)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)