> Markdown version of [/jobs/ext/2594871-machine-learning-engineer-foundation-model-services](https://www.wearedevelopers.com/jobs/ext/2594871-machine-learning-engineer-foundation-model-services). 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, Foundation Model Services - **Company:** Apple Inc. - **Location:** Seattle, WA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Amazon Web Services, App Store (IOS), Microsoft Azure, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Google Cloud, Cloud Platform System, Large Language Models, Siri, Kubernetes, Information Technology, Low Latency, Build Tools, Machine Learning Operations, TensorRT, Docker, Programming Languages - **Published:** August 13, 2026 - **Apply:** https://www.seattlejobs.com/job.asp?id=3351754384&tx=IT9184THV&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 2+ years of industry experience building and shipping production software and/or machine learning systems. * Proficiency in a modern programming language such as Go or Python. * Experience deploying and operating services on a cloud platform (AWS, Azure, GCP, or equivalent) using containers and Kubernetes/Docker. * 5 year+ industry experience in ML technologies (LLMs, Machine Learning, NLP, Information Retrieval, Statistics). * Experience building or operating high-throughput, low-latency services. * Strong communication and collaboration skills, with the ability to partner across research and product teams. * Bachelor's degree or higher in Computer Science or related technical field. Preferred Qualifications * Familiarity with Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc. ## Description Do you think differently? Are you eager to break the status quo, bold and ambitious, unafraid to take risks, and passionate about building best-in-class technology? If so, there's no better place to do it than Apple. The Foundation Model Services team builds the frameworks, services, and tools that run Apple's largest foundation models in production. Our infrastructure powers intelligent experiences across products people use every day - Search, Music, TV, the App Store, Messages, Photos, Spotlight, Safari, Siri, and more - serving millions of queries at incredibly low latency while drawing every ounce of performance from our hardware. Join us and you'll help bring intelligence to billions of users around the world, working on optimizing and serving large language, vision, and speech models at Apple's scale., Work closely with product teams to build production-grade solutions that launch models serving customers in real time. Partner with foundation model researchers to prototype and develop inference for cutting-edge model architectures, and build tools that help us understand and remove performance bottlenecks across different hardware and use cases. Write high-quality code, learn quickly in a fast-moving field, and grow your impact as you take on larger pieces of the system. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Lessons from Steve Jobs - Learnings from the Past for the Future](https://www.wearedevelopers.com/videos/1021-lessons-from-steve-jobs-learnings-from-the-past-for-the-future) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)