8 hours ago
San Jose, CA, USASenior
Responsibilities
- Architect and optimize LLM, quantized-model, and emerging AI workloads for AMD GPU architectures.
- Design, implement, profile, and optimize high-performance GPU kernels.
- Analyze compute, memory bandwidth, cache hierarchy, synchronization, scheduling, and execution efficiency to eliminate performance bottlenecks.
- Develop compiler-level optimizations and code-generation techniques using LLVM, MLIR, and related technologies.
- Build AI-powered coding agents and automation workflows for kernel generation, optimization, benchmarking, and validation.
- Collaborate with GPU architecture, compiler, library, framework, model, and infrastructure teams to improve end-to-end AI system performance.
- Provide technical leadership, define goals and scope, and independently drive development efforts and initiatives.
Requirements
- Bachelor's or master's degree in computer engineering, computer science, or a related field.
- Strong C++ and/or Python skills.
- Strong experience developing and optimizing GPU kernels using HIP, CUDA, C, C++, or similar technologies.
- Solid understanding of GPU compute, memory hierarchy, cache behavior, synchronization, and performance bottlenecks.
- Strong analytical and problem-solving skills with attention to detail.
- Ability to work independently, self-start, and drive tasks to completion.
Benefits
- AMD benefits are described in the AMD benefits at a glance resource.
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.