- Conduct performance studies to inform and validate architecture decisions.- Create optimized implementations of machine learning workloads on Apple Silicon including Neural Engine GPU and CPU.- Collaborate with system teams to create performance models of emerging AI/ML techniques and analyze system architecture trade-offs.- Work with software development tools teams to deliver performance analysis instruments and optimized libraries and frameworks for AI/ML applications.
- Bachelors degree or equivalent job-related experience in Computer Engineering Computer Science or a related field.
- Knowledge of computer architecture fundamentals.
- Proficiency in some of the C/C family programming languages and scripting languages such as Python.
- Experience in software development for at least one of the following hardware IPs: AI/ML HW accelerators GPUs processing units image/video encoders or similar.
- M.S. or Ph.D. in Computer Science Computer Engineering Electrical Engineering or a closely related field.
- 10 years of relevant experience in software performance optimization performance analysis tools performance optimization process and development of efficient computational algorithms.
- Ability to prototype and benchmark algorithms on CPU GPU and Neural Engine platforms analyze performance metrics and create high-level complexity models.
- Experience with AI/ML graphics or HPC performance benchmarks and workloads.
- Proficiency in popular AI/ML frameworks such as PyTorch and relevant software stacks.
- Experience in developing highly efficient low-level performance libraries for AI/ML accelerators or GPUs.
- Knowledge of operating system internals and compiler technologies.
- Technical aptitude and curiosity as well as ability to collaborate effectively with team members partners and stakeholders.
- Conduct performance studies to inform and validate architecture decisions.- Create optimized implementations of machine learning workloads on Apple Silicon including Neural Engine GPU and CPU.- Collaborate with system teams to create performance models of emerging AI/ML techniques and analyze syst...
- Conduct performance studies to inform and validate architecture decisions.- Create optimized implementations of machine learning workloads on Apple Silicon including Neural Engine GPU and CPU.- Collaborate with system teams to create performance models of emerging AI/ML techniques and analyze system architecture trade-offs.- Work with software development tools teams to deliver performance analysis instruments and optimized libraries and frameworks for AI/ML applications.
- Bachelors degree or equivalent job-related experience in Computer Engineering Computer Science or a related field.
- Knowledge of computer architecture fundamentals.
- Proficiency in some of the C/C family programming languages and scripting languages such as Python.
- Experience in software development for at least one of the following hardware IPs: AI/ML HW accelerators GPUs processing units image/video encoders or similar.
- M.S. or Ph.D. in Computer Science Computer Engineering Electrical Engineering or a closely related field.
- 10 years of relevant experience in software performance optimization performance analysis tools performance optimization process and development of efficient computational algorithms.
- Ability to prototype and benchmark algorithms on CPU GPU and Neural Engine platforms analyze performance metrics and create high-level complexity models.
- Experience with AI/ML graphics or HPC performance benchmarks and workloads.
- Proficiency in popular AI/ML frameworks such as PyTorch and relevant software stacks.
- Experience in developing highly efficient low-level performance libraries for AI/ML accelerators or GPUs.
- Knowledge of operating system internals and compiler technologies.
- Technical aptitude and curiosity as well as ability to collaborate effectively with team members partners and stakeholders.
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