At Apple our Platform Architecture group is responsible for connecting our hardware and software into one unified system. Youll collaborate with engineers across Apple to design how our technologies work in unison drive development of our renowned system-on-a-chip architecture and forward-looking prototype systems. Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture system software and algorithm teams to develop integrated highly optimized solutions for machine learning applications.
In this role you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will critically evaluate ML model optimization techniques from the literature analyzing what works and why and proposing new ideas that build on what you learn. You will gain insights on how to make workloads run efficiently on our SoCs and provide guidance to software and algorithm teams.
Create optimized implementations of ML workloads on Apple silicon including Neural Engine GPU and with IP and SoC architecture teams to develop performance models and simulations of future with system teams to create high-level performance models of emerging ML techniques and analyze system architecture emerging ML model optimization techniques through experimentation and analysis; propose new ideas to inform hardware and algorithm direction.
Bachelors degreenExperience in C/C and/or PythonnExperience in hardware IPs: ML HW accelerators GPU/CPU image/video processors or with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
MS or PhD in EE/CE/CS or related fieldn20 years of relevant experiencenExperience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environmentsnExperience designing experiments to evaluate ML model optimization techniquesnAbility to prototype algorithms on CPU/GPU/Neural Engine analyze performance metrics and create high-level complexity modelsnVerbal and written communication skills for collaborating with partner teamsnUnderstanding of compilers
Required Experience:
Staff IC
At Apple our Platform Architecture group is responsible for connecting our hardware and software into one unified system. Youll collaborate with engineers across Apple to design how our technologies work in unison drive development of our renowned system-on-a-chip architecture and forward-looking pr...
At Apple our Platform Architecture group is responsible for connecting our hardware and software into one unified system. Youll collaborate with engineers across Apple to design how our technologies work in unison drive development of our renowned system-on-a-chip architecture and forward-looking prototype systems. Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture system software and algorithm teams to develop integrated highly optimized solutions for machine learning applications.
In this role you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will critically evaluate ML model optimization techniques from the literature analyzing what works and why and proposing new ideas that build on what you learn. You will gain insights on how to make workloads run efficiently on our SoCs and provide guidance to software and algorithm teams.
Create optimized implementations of ML workloads on Apple silicon including Neural Engine GPU and with IP and SoC architecture teams to develop performance models and simulations of future with system teams to create high-level performance models of emerging ML techniques and analyze system architecture emerging ML model optimization techniques through experimentation and analysis; propose new ideas to inform hardware and algorithm direction.
Bachelors degreenExperience in C/C and/or PythonnExperience in hardware IPs: ML HW accelerators GPU/CPU image/video processors or with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
MS or PhD in EE/CE/CS or related fieldn20 years of relevant experiencenExperience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environmentsnExperience designing experiments to evaluate ML model optimization techniquesnAbility to prototype algorithms on CPU/GPU/Neural Engine analyze performance metrics and create high-level complexity modelsnVerbal and written communication skills for collaborating with partner teamsnUnderstanding of compilers
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar
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