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AMD
San Jose, California
Source: AMD careers · View original posting
From AMD's posting. “We” and “our” refer to the employer.
Senior level engineer who will be responsible for driving AMD’s strategy, architecture, optimization and tooling to achieve industry-leading AI Pre-training and Distributed Inference Performance on AMD GPU. You will partner across hardware architecture, AI frameworks, compilers, runtime, ROCm, developer tools and model to scale performance analysis and optimization.
As an engineer of Collectives and Network performance, you will help drive the end-to-end technical performance attainment across the entire software stack focusing on getting the best performance on multiple generations of AMD GPUs with wide range of models including latest state-of-the-art AI models. You will help set the strategy and roadmap for general optimization, accelerating supporting new models and out of box performance.
If you are passionate about performance optimization, getting the best out of the hardware, and shaping the future of AI acceleration, then this role is for you.
The ideal candidate will have deep knowledge with Network, NIC and GPU hardware architecture, software optimization, performance modeling, AI frameworks and latest trend in inference and training optimization. Hand-on experience in mapping model architecture to low level software, hardware and understanding the impact of each layer of the stack on model performance. Strong knowledge in latest generative model architecture, especially SoTA models, distributed inference and deployment at scale is crucial.
Senior level engineer who will be responsible for driving AMD’s strategy, architecture, optimization and tooling to achieve industry-leading AI Pre-training and Distributed Inference Performance on AMD GPU. You will partner across hardware architecture, AI frameworks, compilers, runtime, ROCm, developer tools and model to scale performance analysis and optimization.
As an engineer of Collectives and Network performance, you will help drive the end-to-end technical performance attainment across the entire software stack focusing on getting the best performance on multiple generations of AMD GPUs with wide range of models including latest state-of-the-art AI models. You will help set the strategy and roadmap for general optimization, accelerating supporting new models and out of box performance.
If you are passionate about performance optimization, getting the best out of the hardware, and shaping the future of AI acceleration, then this role is for you.
The ideal candidate will have deep knowledge with Network, NIC and GPU hardware architecture, software optimization, performance modeling, AI frameworks and latest trend in inference and training optimization. Hand-on experience in mapping model architecture to low level software, hardware and understanding the impact of each layer of the stack on model performance. Strong knowledge in latest generative model architecture, especially SoTA models, distributed inference and deployment at scale is crucial.
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