On-device ML Infrastructure Engineer, Orchestration & Performance

What you'll do

• Drive full-stack changes through the OS and tooling to deploy large SOTA models across the Apple Silicon ecosystem.
• Implement mechanisms to support efficient orchestration of models across Apple Silicon hardware.
• Modify authoring and MLIR-based compilers to expose mechanisms for state-of-the-art model execution.
• Develop optimization toolkits for model compression and acceleration.
• Build ML compilers and runtimes for efficient execution on embedded systems.
• Create comprehensive benchmarking and debugging toolchains for machine learning workflows.
• Support advanced use cases for Siri, Apple Intelligence, and Camera through framework improvements.

What we're looking for

• 3-5 years of experience 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.
• Experience working on or adjacent to MLIR-based compilers (preferred).
• Familiarity with deploying applications or tooling on Apple platforms (preferred).
• Familiarity with programming paradigms for the GPU, CPU, and Neural Engine (preferred).
• Familiarity with writing kernels for ML model execution (preferred).