5 days ago
Responsibilities
- Analyze latency, memory, power, and numerical correctness of machine learning models running on Apple devices.
- Optimize ML inference performance across CPU, GPU, and Apple Neural Engine hardware.
- Implement models in the ML software stack and perform model import and conversion.
- Write Python, C++, and shell scripts and build utilities and debugging tools for performance and power analysis.
- Generate, extract, analyze, and report performance and power metrics for Apple hardware.
- Collaborate with research, software engineering, hardware engineering, and product teams.
Requirements
- Experience with ML inference, quantization, and performance-versus-accuracy tradeoffs.
- Familiarity with ML architectures such as large language models, diffusion models, and convolutional neural networks.
- Knowledge of operating systems, embedded systems, and CPU, GPU, SoC, memory, and computer architectures.
- High proficiency in Python, C++, and shell scripting.
- Familiarity with Linux or macOS.
- Strong verbal and written communication skills, including the ability to summarize, present, and lead group discussions.
- Preferred: Master's or PhD in computer science or a related discipline.
- Preferred: Experience with Core ML, MPS Graph, Metal Performance Shaders, MLX, PyTorch, TensorFlow, JAX, TFLite, ONNX, ExecuTorch, MLIR, LLVM, or TVM.
- Preferred: Experience implementing high-performance compute kernels for CPUs, GPUs, or AI accelerators.
- Preferred: Experience with Xcode, Swift, Objective-C, or on-device ML stacks.
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About Apple
We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. And the same innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it. This is where your work can make a difference in people’s lives. Including your own. Apple is an equal opportunity employer that is committed to inclusion and diversity. Visit apple.com/careers to learn more.