Datacenter GPU Engineer for AI/ML Deployments (Onsite)

Advanced Micro Devices; Temple, Northern (TX, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

AMD Benefits

Job summary

Advanced Micro Devices (AMD) is seeking a senior engineer to lead our datacenter graphics hardware/software subsystem projects for OEM partners and enterprise customers in Temple, TX. You will apply expertise in AI/ML, virtualization, and server GPU deployment to enable high-performance compute workloads.

In this role you’ll collaborate across teams, install and validate software on GPU/compute clusters, guide customers, and help drive hardware bring-up through end-of-life support.

Qualifications

• Bachelor’s or Master’s in CS/EE or equivalent.
• Experience with datacenter GPU/software stacks and virtualization.
• Strong debugging, analytical and communication skills.

Responsibilities

• Perform node and cluster-level software installation and validation for GPU/compute AI projects.
• Resolve technical issues for customers using AMD Instinct products.
• Provide technical guidance and support for server graphics and compute projects.
• Build datacenter GPU containers for customer testing and deployment.
• Qualify new software functionality for compatibility with customer requirements.
• Collaborate with PMs to maintain schedules and deliverables.

Skills

Datacenter deployment

GPU/AI/ML systems

Linux administration

Troubleshooting

Networking

Project management

Education

Bachelor’s degree in Computer Engineering / Electrical Engineering / CS

Master’s degree (optional)

Tools

VMware

KVM

Docker

ROCm

Job description

Advanced Micro Devices (AMD) is seeking a senior engineer to lead our datacenter graphics hardware/software subsystem projects for OEM partners and enterprise customers in Temple, TX. You will apply expertise in AI/ML, virtualization, and server GPU deployment to enable high-performance compute workloads.

In this role you’ll collaborate across teams, install and validate software on GPU/compute clusters, guide customers, and help drive hardware bring-up through end-of-life support.