Senior Staff Software Development Engineer at AMD focused on optimizing and developing deep learning frameworks for AMD GPUs. The role involves enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems, collaborating with internal library teams and open-source maintainers. Key responsibilities include end-to-end optimization of distributed inference and RL solutions, optimizing performance on distributed computing environments, and leveraging compiler technologies. Requires strong C++ development in Linux, GPU kernel development, deep learning integration, and high-performance computing experience.

Senior Software Engineer focused on NPU firmware and AI acceleration, implementing features for efficient ML workload inferencing on NPU hardware, debugging applications and firmware, and contributing to future architecture.

Principal Software Engineer focused on optimizing AI inference performance and distributed systems at AMD, working with the latest hardware and software technologies. Responsibilities include developing techniques for scale-up/scale-out inference, creating methods and tooling for dynamic resource utilization in inference, and supporting the ROCm ecosystem.

This role focuses on designing, testing, and validating reference architectures for large-scale AI training and inference clusters. The engineer will develop tools for efficient cluster management, create documentation, serve as a technical interface with customers, conduct proof-of-concept implementations, and evaluate/benchmark infrastructure performance. Expertise in Kubernetes, AI/ML workloads, datacenter networking, GPU computing, and performance optimization for inference deployments is required.

Software Development Engineer at AMD to research, design, develop, and test operating systems-level software, compilers, and network distribution software for semiconductor operations. Focus on analyzing shader algorithms, optimizing performance, and developing algorithms/shaders for performance improvement on GPUs, including Machine Learning pipelines.

Software Development Engineer at AMD focused on developing AI software for GPU kernel optimization using LLM-powered agents, compiler feedback, and reward-driven loops. Also involved in developing AI systems courses on GPU optimization, transformers, and reinforcement learning, with project management responsibilities.

Sr. Software Development Engineer at AMD to research, design, develop, and/or test operating systems-level software, compilers, and/or network distribution software for semiconductor operations. The role involves developing software and tools for design, infrastructure, and technology platforms, with a focus on AI and next-generation computing experiences. Requires experience with ML model serving frameworks, multi-GPU inference, and GPU architecture.

Sr. Software Development Engineer at AMD (Xilinx) to research, design, develop, and test operating systems-level software, compilers, and network distribution software for semiconductor operations. Focus on machine learning model development, optimization, quantization, pruning, code generation, and acceleration platforms (GPU, TPU, APU, FPGAs) for LLMs.

Lead Runtime Engineer at AMD to support and develop GPU-compute language runtime libraries for the ROCm platform on Windows, focusing on AI and HPC applications. Involves deep technical collaboration with customers and partners to resolve driver-level challenges and ensure successful deployment of AMD GPU technologies.

Sr. Manager AI Systems Validation Architect at AMD, responsible for company-level technical leadership in defining how AMD validates AI platforms as complete, deployable solutions. This role shapes validation strategy at the architectural level, ensuring alignment across CPU, GPU, networking, system architecture, and software domains. The position involves leading and managing a small team of senior architects, with hands-on involvement when needed, and serving as a recognized authority in system-level validation architecture for AMD’s AI platforms.

This role focuses on enabling and supporting server OEMs, ODMs, and MDCs by ensuring the platform enablement, solutions ramp, and product support for AMD server products, including those used for AI training and inference. The engineer will test AMD's customer enabling collaterals and platform engineering ingredients against vertical industry solutions, work with internal teams to establish best-known-configurations, utilize pre-production hardware to uncover and solve system integration issues, and support customer debug. The role requires a Bachelor's or Master's in electrical engineering, computer engineering, or comparable disciplines.

Senior Staff Software Development Engineer focused on ML/AI runtime optimization, system-level model integration, and accuracy debugging for hardware implementation. The role involves analyzing and resolving complex issues in AI models, identifying and fixing accuracy problems in quantized or modified models, building diagnostic tools, and supporting hardware debugging and performance improvements.

This role is for a Sr. Manager in the HPC & AI Applications Engineering team at AMD. The candidate will lead a team of experts to adapt and optimize HPC and AI applications for AMD hardware, develop performance models, and drive the delivery of Exascale-ready applications. The role requires strong technical leadership, customer interaction, and a demonstrated track record in software team management. A PhD in a relevant scientific or engineering domain is preferred.

Software Development Engineer to research, design, develop, and/or test operating systems-level software, compilers, and/or network distribution software for semiconductor operations. This role involves designing, developing, troubleshooting, and debugging software programs for enhancements and new products, including software and tools for design, infrastructure, and technology platforms. The engineer will determine hardware compatibility and influence hardware design, working on complex system-level software problems with limited supervision. Requires experience in C/C++, CUDA, 2D/3D graphics, GPU architecture/programming, machine learning, object-oriented design, memory management, multi-threading, and the GNU toolchain.