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Apple ML Compute Acceleration Engineer United States, California, Cupertino 58006279
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Responsibilities: * Adding optimizations in machine learning computation graph. * Defining and implementing APIs in Metal Performance Shaders Graph, investigating new algorithms. * Developing and maintaining MLIR dialect in Apple and open source with upgrades using latest LLVM. * Performing in-depth analysis, compiler and kernel level optimizations to ensure the best possible performance across hardware families. * Tune GPU and Neural Engine accelerated compute across products. * Tuning the cost model and optimizing runtime dispatch to multiple IPs to get best performance on Apple Silicon.Intended deliverables: * GPU Compute acceleration technology. * Apple Intelligence implementation and acceleration. * Optimized compute graphs across products.
- Proven programming and problem-solving skills.
- Good understanding of machine learning fundamentals.
- GPU compute programming models & optimization techniques.
- GPU compute framework development, maintenance, and optimization.
- Experience with system level programming and computer architecture.
- Experience with high performance parallel programming, GPU programming or LLVM/MLIR compiler infrastructure is a plus.
- Background in mathematics, including linear algebra and numerical methods.
- Strong communication and collaboration skills.
- Strong background of building high performance, production quality software on schedule.
- Experience with compiler technologies.
- Experience with adding computational graph support, runtime or device backend to Machine learning libraries (TensorFlow, PyTorch or JAX) support is a plus.
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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