9 days ago
China (city not specified)Senior
Responsibilities
- Optimize TensorFlow, PyTorch, vLLM, and SGLang for AMD GPUs and contribute improvements upstream.
- Develop and tune high-performance GPU kernels and operators to improve throughput and latency.
- Adapt and optimize Llama, Qwen, and DeepSeek architectures using techniques including FlashAttention, PagedAttention, continuous batching, speculative decoding, and quantization.
- Profile and optimize compute, memory, and communication performance across multi-GPU and multi-node systems.
- Use compiler technologies and graph compilers to accelerate deep learning training and inference pipelines.
- Prototype and integrate advanced optimization methods into production systems.
- Collaborate with internal GPU library teams and open-source maintainers to support upstream integration.
- Deliver maintainable, reliable, and production-quality performance-critical software.
Requirements
- Strong practical experience with vLLM or SGLang and modern LLMs such as DeepSeek and Qwen.
- Strong theoretical knowledge of Transformer, Attention, Mixture-of-Experts, and KV Cache concepts.
- Hands-on experience with FlashAttention, PagedAttention, continuous batching, and INT8, INT4, GPTQ, or AWQ quantization.
- Experience profiling and optimizing compute, memory, and communication bottlenecks in multi-GPU and multi-node environments.
- Expertise running and optimizing large-scale workloads on heterogeneous clusters.
- Experience integrating optimized GPU kernels into TensorFlow or PyTorch for large-scale training and inference.
- Expert Python and C++ programming skills, debugging and testing experience, and a record of delivering maintainable performance-critical software.
- Open-source contribution experience and strong self-motivation.
- Bachelor’s and/or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- Preferred experience with AMD GPU kernel development using HIP, CUDA, assembly language, CK, CUTLASS, or Triton, and knowledge of GCN or RDNA architectures.
- Preferred knowledge of LLVM, ROCm, TVM, or MLIR and distributed inference methods such as tensor parallelism and pipeline parallelism.
Benefits
- AMD benefits are referenced through the company’s benefits overview, but specific benefits are not listed.
- The posting is for an existing vacancy.
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.