The role at AMD involves optimizing and developing deep learning frameworks specifically for AMD GPUs. As a core team member, you will enhance GPU kernels and improve training and inference performance across multi-GPU and multi-node systems. The position requires collaboration with internal GPU library teams and open-source maintainers to ensure effective integration of optimizations. The ideal candidate will provide technical leadership and drive projects independently within a high-performing team.

• Master's or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Advanced technical and analytical skills in Linux environments.
• Deep expertise in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly.
• Advanced proficiency in Python and C++ with experience in performance tuning and debugging.
• Broad experience with large-scale heterogeneous compute environments.

• Enhance and optimize deep learning frameworks like TensorFlow and PyTorch for AMD GPUs.
• Create and optimize GPU kernels to maximize performance for specific AI operations.
• Design and optimize deep learning models specifically for AMD GPU performance.
• Collaborate with internal teams to analyze and improve training and inference performance on AMD GPUs.
• Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.
• Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.
• Leverage advanced compiler technologies to improve deep learning performance.
• Enhance the full deep learning pipeline, including integrating graph compilers.
• Apply sound engineering principles to ensure robust and maintainable solutions.
• Provide strategic direction and mentorship to junior team members through code reviews and knowledge sharing.

• AMD provides a competitive 'Total Rewards' package that focuses on financial growth, health, and work-life balance.