AI Systems Engineer - HPC

Advanced Micro Devices, Inc•San Jose, CA

3d•Onsite

About The Position

At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we’re looking for talent who feel the same: people who want to leave the planet better than they found it, those who don’t shy away from humanity’s challenges but are determined to help solve them. AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you’re designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward. We are seeking an AI Systems Engineer to join our AMD IT compute platforms engineering team. The AI Systems Engineer is responsible for the design, development, and administration of High-Performance Computing (HPC) infrastructure, GPU clusters, and AI workload schedulers.

Requirements

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