HPC Systems Staff Engineer

AMD•San Jose, CA

2d•Hybrid

About The Position

HPC Systems Staff Engineer WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. THE ROLE: We are seeking an HPC Systems Engineer to join our AMD IT compute platforms engineering team. The Systems Engineer is responsible for the design, development, and administration of High-Performance Computing (HPC) infrastructure, GPU clusters, and AI workload schedulers. THE PERSON: You have a passion for learning. You are passionate about the field of large-scale distributed computing in AI and HPC workloads. You take responsibility for end-to-end outcomes of your efforts. You want to build scalable and highly performant HPC/AI/Data services with AMD hardware, software, people and processes. You have a curiosity to learn and improve scalable HPC systems. You have significant experience in working across a globally distributed organization.

Nice To Haves

Experience in developing Python based AI apps and UI
HPC infrastructure engineering for AI/HPC domain
SLURM and Kubernetes management
Managing GPU clusters optimizing GPU-based services/tools/software
Experience in creating web services with HPC backend (like AI)
Proficiency in RoCEv2, K8s, KVM, Ubuntu, Python, Shell, GPU drivers, and Cluster interconnect with 400G networking.
Demonstrated experience with AI workload schedulers and allocation optimization.
Automation/monitoring tool - Ansible / Saltstack, Terraform, Prometheus, Grafana
Strong organizational, problem-solving, and troubleshooting skills, with the ability to manage multiple projects simultaneously.
Excellent verbal and written communication skills, with the ability to collaborate effectively with team members and stakeholders at all levels of the organization.

Responsibilities

Develop, implement, and maintain GPU-based clusters, ensuring optimal performance
Administer ML/AI platforms - Distributed ML services, LLMs and AI inferencing, by managing deployments, resource allocation, monitoring, and security.
Automate system provisioning and Cluster management end to end
Collaborate with cross-functional teams to address AI infrastructure requirements, support AI-related projects, and provide technical expertise.
Monitor and evaluate the performance of AI systems and clusters, ensuring that they adhere to industry best practices and meet company standards.
Use AI/ML to continuously improve internal processes and tools that are used in end-to-end delivery of your services in this team