On-Device ML Quality Infrastructure Engineer

Summary: The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products.

The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple’s critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.

Our group is looking for an On-Device ML Quality Infrastructure Engineer. The role involves building and maintaining the infrastructure used to connect, validate, and benchmark the components of the On-Device Machine Learning stack.

Description: We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis.

As an engineer in this role, you will build and maintain the infrastructure that keeps every component of our ML stack robust and testable, and that lets our engineers move fast without breaking things. This means owning build and CI systems, developing automation frameworks, and ensuring high-quality, low-friction workflows from commit to validation.

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