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ul candidate will: - Analyze the performance of linear algebra and machine learning algorithms on Apple GPU platforms, pursuing investigations wherever they take you in Apple software - With our partner teams in Software Engineering and Hardware Technologies, formulate system-level strategies to address performance problems and unlock the next level of AI performance for our users - Help build the prototype software implementation, for simulated future hardware, then communicate what we learned to teams building production software for products
Minimum Qualifications
BS degree
Experience with software and hardware performance analysis and optimization
Experience in GPU programming models such as Metal, CUDA, or similar
Preferred Qualifications
MS or PhD in Computer Science, Electrical Engineering, or equivalent
15 years of relevant industry experience
Experience with the internals of GPU drivers, compilers and/or accelerated libraries
Experience working specifically in CUDA C++ on ML and/or linear algebra algorithms
Experience with distributed algorithms for HPC (for example, supercomputing)
Experience communicating across both hardware and software organizations
Additional Requirements
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