GPU Acceleration Engineer
3 days ago
Join us at Apple as a GPU Acceleration Engineer and be part of our innovative team that provides GPU acceleration for popular Machine Learning libraries such as TensorFlow, PyTorch, and JAX using Metal runtime and device backend.
The successful candidate will have experience in designing and developing compiler-based optimizations for Metal backend in ML frameworks such as torch.compile for PyTorch, working on cutting-edge ML inference framework project, optimizing code for efficient and scalable ML inference using distributed techniques, implementing features of Metal device backend for ML training acceleration technologies, and collaborating with Core teams of PyTorch, JAX, or Tensorflow to provide Metal runtime and device backend support.
You will have the opportunity to work on advanced algorithms and data structures, collaborate with top engineers, and contribute to the development of world-class machine learning solutions. Our ideal candidate will have 3+ years of programming and problem-solving experience with C/C++/ObjC, experience with Distributed training or inference techniques, GPU compute programming models & optimization techniques, and experience with system level programming and computer architecture.
Responsibilities:
- Design and develop compiler-based optimizations for Metal backend in ML frameworks
- Work on cutting-edge ML inference framework project
- Optimize code for efficient and scalable ML inference using distributed techniques
- Implement features of Metal device backend for ML training acceleration technologies
- Collaborate with Core teams of PyTorch, JAX, or Tensorflow to provide Metal runtime and device backend support
Preferred Qualifications:
- Contributions to an AI framework such as PyTorch, JAX, or Tensorflow
- Experience with graph compilers such as Triton, OpenXLA, or LLVM/MLIR
Estimated Salary: $150,000 - $220,000 per year
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