Advanced Micro Devices, Inc

AI Research Infrastructure Engineer

Advanced Micro Devices, Inc$120K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years experience in AI/ML/HPC infrastructure operations.
  • Strong Linux systems administration skills in multi-user production environments.
  • Hands-on experience managing SLURM workload and optimizations.
  • Understanding of GPU, HPC, or AI/ML research environments.
  • Knowledge of automation tools and monitoring systems.
  • Familiarity with Docker, Kubernetes, and modern engineering workflows.

Responsibilities

  • Manage daily operations of SLURM-managed GPU and HPC clusters.
  • Collaborate with researchers to optimize multi-GPU/multi-node workloads.
  • Enhance compute platform reliability, including shared storage and networking.
  • Support GPU platform readiness through validation and debugging.
  • Oversee AMD's university program clusters and external academic interfaces.
  • Lead incident response efforts and create reliability practices.
  • Implement agentic workflows to streamline infrastructure management.

Benefits

  • Comprehensive health, dental, and vision insurance.
  • Retirement savings plan with employer matching.
  • Generous paid time off policy and holidays.
  • Continuous learning and development opportunities.
Full Job Description
THE ROLE:

We are seeking an AI Research Infrastructure Engineer to operate, scale, and continuously improve the shared GPU and HPC compute platform behind our AI, ML, and HPC research. You will own the day-to-day health of our SLURM and GPU clusters and work hands-on with researchers to get demanding workloads-including large-scale multi-GPU and multi-node training-running reliably and efficiently.

This is a research-enablement role, not a traditional systems-administration role. It requires research literacy-a working understanding of how modern models are trained and where they bottleneck-so you can partner with researchers as a technical peer and directly accelerate their work. The focus is on enabling and operating research infrastructure, not pursuing an independent research agenda.

Your scope spans both internal and externally visible compute clusters across the research organization, including AMD's university program clusters and interfacing with external academic collaborators. You may also help coordinate the contractors and systems administrators supporting the environment. Familiarity with modern agentic engineering workflows-tools such as Claude Code, Codex, or Cursor-is also expected.

THE PERSON:

The ideal candidate should be passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.

KEY RESPONSIBILITIES:
  • Own day-to-day operations of the SLURM-managed GPU and HPC clusters, ensuring high availability, utilization, and performance across a multi-user research environment.
  • Partner directly with researchers as a technical peer to get demanding multi-GPU and multi-node workloads running and optimized.
  • Operate and improve the broader compute platform-shared storage, networking, containers, and monitoring-and build automation and self-service workflows that reduce friction for researchers.
  • Support GPU platform and hardware bring-up: validation, enablement, debugging, and operational readiness.
  • Manage AMD's university program clusters and support external academic collaborators alongside internal research users, spanning both internal and externally visible compute clusters.
  • Lead incident response and root-cause analysis, and build runbooks and preventive practices to improve reliability.
  • Set operational standards and best practices, and help coordinate the contractors and systems administrators supporting the environment.
  • Apply agentic coding and operations workflows to improve velocity across deployment, troubleshooting, documentation, and infrastructure management.

Experience:
  • Operations- and infrastructure-minded, with a strong bias toward reliability, automation, usability, and reducing operational overhead for researchers.
  • Strong hands-on Linux systems administration in shared/multi-user, production compute environments.
  • Practical, hands-on experience with the SLURM workload manager-partitions, scheduling policy, accounting, node management, and tuning.
  • Experience operating GPU, HPC, or AI/ML research compute environments.
  • Research literacy: a working understanding of how large models are trained and where they bottleneck, alongside researchers as a technical peer on multi-GPU/multi-node workloads.
  • Experience with Docker/containers and Kubernetes, plus automation and system health monitoring.
  • Familiarity with agentic engineering workflows using tools such as Claude Code, Codex, or Cursor.

Preferred:
  • DevOps practices: GitHub Actions, self-hosted runners, CI/CD pipelines, and infrastructure automation / Infrastructure as Code.
  • Container registries and reproducible runtime environments.
  • Shared storage, networking, and high-speed interconnects (InfiniBand, RoCE) in multi-user clusters.
  • AMD GPU platforms and the ROCm/RCCL stack-hardware bring-up, architecture-aware debugging, validation, or performance workflows.
  • Supporting developer- or researcher-facing platforms.

ACADEMIC CREDENTIALS:

Bachelor's or master's degree in computer science, computer engineering, electrical engineering, or equivalent preferred

LOCATION:

Austin, TX

This role is not eligible for visa sponsorship.

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Benefits offered are described: AMD benefits at a glance.

About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ

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