On-Device ML Infrastructure Engineer (Core ML Framework)

Apple • Cupertino, CA

74d

About The Position

This is a fantastic opportunity to join the On-Device Machine Learning team at Apple. This team enables the Research to Production lifecycle of innovative 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 is central to that field, collaborating with research, SW engineering, HW engineering, and products. The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to implement 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 ML Infrastructure Engineer, with a focus on the development of Apple's Core ML framework. The role entails designing, implementing and maintaining APIs for on-device model execution. We are building an 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. This role focuses on the Core ML framework APIs for execution on-device. We're looking for a highly motivated software engineer that is creative, and passionate about providing high quality developer tools and APIs in the fast paced and dynamic space of ML.

Requirements

• Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch).
• Knowledge of general ML Framework implementation (Jax, PyTorch, or TensorFlow).
• Experience with MLIR / LLVM compiler technologies.
• BS/MS/PhD in Computer Science or Electrical Engineering.

Responsibilities

• Design, implement and maintain APIs for on-device model execution.
• Build critical infrastructure for onboarding machine learning architectures to Apple devices.
• Develop optimization toolkits for machine learning models.
• Implement machine learning compilers and runtimes for efficient model execution.
• Create benchmarking, analysis and debugging toolchains for model iterations.
• Enhance the end-to-end developer experience for ML development.

What This Job Offers

• Industry: Computer and Electronic Product Manufacturing
• Education Level: Master's degree
• Number of Employees: 5,001-10,000 employees