1 day ago
São Paulo, BrazilSenior
Responsibilities
- Optimize TensorFlow and PyTorch deep learning frameworks for AMD GPUs.
- Design and optimize GPU kernels for AI operations using low-level programming techniques.
- Develop and optimize deep learning models for AMD GPU performance.
- Improve training and inference performance across multi-GPU and multi-node systems.
- Collaborate with internal GPU library teams and open-source maintainers to integrate and upstream optimizations.
- Use compiler technologies and graph compilers to improve the deep learning pipeline.
- Apply software engineering practices for robust and maintainable solutions.
Requirements
- Expertise in designing and optimizing GPU kernels for deep learning on AMD GPUs.
- Experience with HIP, CUDA, assembly, AMD GCN and RDNA architectures, Compute Kernel, CUTLASS, and Triton.
- Experience integrating optimized GPU performance into TensorFlow or PyTorch for model training and inference.
- Expertise in Python and C++, including debugging, performance tuning, and test design.
- Experience running large-scale workloads on heterogeneous compute clusters.
- Foundational understanding of compiler theory and tools such as LLVM and ROCm.
- Bachelor’s or master’s degree in computer science, computer engineering, electrical engineering, or a related field.
Categories
About AMD
AMD designs and sells CPUs, GPUs, and adaptive/embedded computing products for PCs, data centers, gaming, and edge devices. Its portfolio includes Ryzen and EPYC processors, Radeon and Instinct graphics, and adaptive SoCs from its Xilinx acquisition, sold to OEMs, cloud providers, and device makers. Founded in 1969 and headquartered in Santa Clara, it is a public company on NASDAQ and supplies semi-custom chips for major game consoles.