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Apple On-device ML Infrastructure Engineer Compiler Frontend United States, California, Cupertino 812347609
09.06.2025
Our group is looking for an ML Infrastructure Engineer, with a focus on ML model semantics and frontend stages of ML compilation. The role is responsible for working with ML research and Applied research engineers to onboard the newest ML architectures to CoreML’s ML model representation, including evolving the representation to support the latest and greatest features in the authored ML program (e.g., PyTorch), and develop the frontend stages of CoreML’s model compilation pipelines.
As an engineer in this role, you will be primarily focused on the ingestion and optimization of ML programs from different authoring frameworks (such as PyTorch) into CoreML using a combination of graph capture, conversion, and compilation pipelines.KEY RESPONSIBILITIES:- Develop technologies to quickly onboard new ML models to our on-device stack, including contributions to ML authoring frameworks.- Understand different ML operations, architectures, and graph representations in different authoring frameworks. Keep abreast of latest innovations in this space.- Architect and build CoreML’s model representation that can efficiently represent program semantics from the authored frameworks, while allowing for peak execution performance. - Define and develop optimizations such as quantization, operator transformations, fusions, etc. to make models more amenable to efficient on-device deployment
- Bachelors in Computer Sciences, Engineering, or related discipline.
- Highly proficient in Python programming, familiarity with C++ is required.
- Proficiency in at least one ML authoring framework, such as PyTorch, TensorFlow, JAX, MLX.
- Strong understanding of ML fundamentals, including common architectures such as Transformers.
- Familiarity with ML and/or traditional compilers.
- Good communication skills, including ability to communicate with cross-functional audiences.
- Experience with any on-device ML stack, such as TFLite, ONNX, etc.
- Experience with designing Python APIs and production deployment of python packages is a strong plus.
- Experience with HuggingFace or any other model repository is a strong plus.
- Experience with MLIR/LLVM or any compiler toolchains is a strong plus.
- Good communication skills, including ability to communicate with cross-functional audiences.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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