AI/HPC Cluster Design Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced AI systems engineer to design scalable AI/HPC clusters with specific focus on compliance with customer and/or design requirements. This role involves reviewing and selecting compute, storage, networking, and power delivery components and solutions to optimize performance and reliability across global deployments. You will collaborate with cross-functional teams to deliver cutting-edge infrastructure for AI and high-performance computing workloads., System Architecture & Design
- Design scalable AI/HPC clusters including compute, storage, and networking
- Evaluate and select CPUs, GPUs, accelerators, interconnects, and memory configurations for optimal cluster performance.
Network
- Design network topologies to maximize overall cluster performance
- Understand the network performance needs of different types of workloads
- Understand advantages and performance trade-offs of network topologies for AI/HPC clusters
Storage
- Design and optimize storage solutions to maximize AI/HPC cluster performance
- Understand advantages and performance trade-offs of cluster storage solutions, e.g. Lustre, Ceph, etc., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
Requirements
An experienced systems engineer with a strong background in HPC, AI systems, and cluster engineering. You bring deep technical knowledge of compute, power, and networking components, a strategic mindset for system-level design, and the ability to collaborate across diverse technical domains. You thrive in fast-paced environments and are passionate about building efficient, scalable, and reliable compute platforms., * Work across multiple organizations with subject matter experts from hardware, software, network, data center, and operations teams to deliver scalable, efficient, and reliable compute infrastructure.
- Experience in HPC, AI systems/clusters, or data center engineering.
- Strong understanding of rack and cluster design
- Knowledge of GPU/CPU architectures, PCIe, UALink, InfiniBand, and Ethernet networking.
- Familiarity with AI/ML frameworks and workload characteristics.
- Excellent problem-solving, communication, and documentation skills.
Preferred Qualifications:
- Experience in HPC, AI infrastructure, or data center systems engineering.
- Experience designing power delivery solutions for racks and data centers
- Contributions to open-source HPC or AI infrastructure projects.
Academic Credentials
Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science or related field.