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Apple On-device ML Infrastructure Engineer 
United States, California, Cupertino 
665133716

03.04.2025
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.- Perform optimizations such as quantization, operator transformations, etc. to make models more amenable to efficient on-device deployment
As an engineer in this role, you will be primarily focused on the interplay between higher-level ML authoring frameworks (such as PyTorch, JAX, MLX, etc.) and Apple’s on-device ML infrastructure. The role requires an understanding of ML modeling (architectures, training vs inference trade-offs, etc.) and ML deployment optimizations (compression, distillation, quantization, hardware optimizations, etc.).
  • 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.
  • Hands on experience working with and/or developing ML optimization techniques such as quantization.
  • Experience with accelerators, GPU programming is a strong plus.
  • Experience with any on-device ML stack, such as TFLite, ONNX, etc.
  • Experience with MLIR compiler stack is a strong plus
  • Good communication skills, including ability to communicate with cross-functional audiences.
  • Excellent communication & interpersonal skills.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.