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On-device ML Infrastructure Engineer (Orchestration & Performance)
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$168,439 / year median in California
Job Description
Cupertino, California, United States Machine Learning and AI Summary Posted:
Sep 02, 2026Weekly Hours:
40Role Number:
200680834-0836 Imagine being at the forefront of an evolution where cutting-edge AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding cutting-edge architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple's machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem.
If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents an exciting opportunity to work on the next generation of intelligent experiences on Apple platforms.
Our group is looking for an ML Infrastructure Engineer, with a focus on model orchestration and performance. The role entails working closely with model authoring, compiler, and runtime teams to ensure that our framework allows executing models with the best stability and performance. Description We're building an end-to-end developer experience for machine learning development that leverages Apple's vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. This role focuses on the core runtime for execution across a wide variety of devices and use cases. We're seeking a highly motivated software engineer who is creative, talented, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning. Responsibilities Drive full-stack changes through the OS and tooling to enable deploying large SOTA models across the Apple Silicon ecosystem, from Apple Watch to Mac Studios. Partner with teams across the company to support advanced use cases for Siri, Apple Intelligence, Camera, and more. Make changes in our authoring and MLIR-based compiler to expose mechanisms for state-of-the-art model execution Implement mechanisms to support efficient orchestration of models across Apple Silicon hardware. Minimum Qualifications 3-5 years working on tooling built in Python 3 and C++/Swift Familiarity with common ML model architectures, execution schemes, and operations. Familiarity with PyTorch or related training frameworks. Preferred Qualifications Experience working on or adjacent to MLIR-based compilers. Familiarity with deploying applications or tooling on Apple platforms. Familiarity with programming paradigms for the GPU, CPU, and Neural Engine. Familiarity with writing kernels for ML model execution. Pay & Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.