Job 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 runtime for execution across a wide variety of devices and use cases. We’re seeking a highly motivated software engineer who is creative, versatile, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning. We have an MLIR-based compiler stack, and use it to target the neural engine, GPU, and CPU in order to harness the full capabilities of the system for ML workflows and execution. 3-5 years working on MLIR-based compilers. Familiarity with common ML model architectures, execution schemes, and operations. Familiarity with C++ Familiarity with PyTorch or related training frameworks Familiarity with Swift. Familiarity with programming paradigms for the GPU, CPU, and Neural Engine. Familiarity with writing kernels for ML model execution.

Requirements

Must-haves

3-5 years working on MLIR-based compilers.
Familiarity with common ML model architectures, execution schemes, and operations.
Familiarity with C++
Familiarity with PyTorch or related training frameworks
Familiarity with Swift.
Familiarity with programming paradigms for the GPU, CPU, and Neural Engine.
Familiarity with writing kernels for ML model execution.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlswift

Platform: apple
Effort: medium