On-Device ML Infrastructure Engineer (CoreML Runtime), Graphics, Games and Machine Learning

Imagine being at the forefront of an evolution where powerful 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 a top destination for

on-device machine learning innovation. Our team builds the essential

infrastructure that enables machine learning at scale on Apple devices. This

involves onboarding innovative 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 on resource-constrained devices and eager to directly

impact how machine learning operates across the Apple ecosystem, this role

presents an incredible opportunity to work on the next generation of intelligent

experiences on Apple platforms. We are seeking an ML Infrastructure Engineer

with a specific focus on graph compilers and runtimes. If you are a highly

motivated software engineer who is creative, versatile, and passionate about

machine learning operator primitives, common compiler optimizations, runtimes,

and system software engineering in the fast-paced and dynamic field of machine

learning, this could be a fantastic role for you.

DESCRIPTION

We’re building an end-to-end developer experience for machine learning

development that employs 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 ML Runtime for execution

on-device.

In this role, you will

• build the world’s most advanced ML graph
• compilation and runtime system, capable of optimizing and delivering ML models
• efficiently on Apple products and services.
• MINIMUM QUALIFICATIONS
• Masters or equivalent experience in Computer Sciences, Engineering, or related
• subject area. Highly proficient in C++ or Swift. Familiarity with Python.
• Experience with any compiler stack (MLIR/LLVM/TVM/...). Familiarity with
• Operating Systems, embedding programming, parallel programming. Sound
• understanding of ML fundamentals, including common architectures such as
• Transformers. Good communication skills, including ability to communicate with
• multi-functional audiences.
• PREFERRED QUALIFICATIONS
• Experience with any on-device ML stack, such as TFLite, ONNX, ExecuTorch, etc.
• Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a
• strong plus. Experience with accelerators, GPU programming is a strong plus.