HPC AI Systems Administrator

MRE Consulting; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits

Professional development support

Job summary

MRE Consulting is seeking a skilled HPC AI Systems Administrator to architect and optimize a secure on-prem AI compute environment. You will enable the Development Team to train and deploy production ML models while enforcing governance and data privacy policies.

The role covers deployment, bare-metal config, GPU driver management, and containerized workloads. Collaboration with Dev teams and vendors is essential to maintain peak performance and security.

Qualifications

• 3+ years of systems administration in Linux-based HPC or enterprise GPU environments.
• Experience with modern enterprise GPU hardware and data center contexts.
• Deep expertise in Linux, container tech, and cluster resource management.

Responsibilities

• Lead deployment, bare-metal configuration, and optimization of on-prem HPC cluster and multi-GPU systems.
• Manage AI software stack, Linux environments, GPU drivers, CUDA/NCCL, and container platforms.
• Implement workload scheduling/orchestration (Kubernetes, Slurm) for efficient resource allocation.
• Establish telemetry/monitoring dashboards for hardware utilization and performance.
• Ensure security/governance, data-at-rest/in-transit baselines, and compliance.
• Coordinate with vendors and integrators for updates and platform maintenance.

Skills

Linux admin

HPC infrastructure

Containerization

Cluster scheduling

Networking

Security governance

Education

Bachelor's degree (CS/CE)

Tools

Docker

Kubernetes

Slurm

Apptainer/Singularity

CUDA drivers

Job description

We are seeking a high-caliber HPC AI Systems Administrator to serve as the foundational architect for our growing AI infrastructure. This role will be responsible for building a secure, scalable, and highly optimized environment to support our corporate data initiatives.

Operating at the critical intersection of infrastructure engineering and software application, you will design and maintain a robust compute platform. Your primary mission is to enable our Development Team to fine-tune and deploy production-level machine learning models smoothly, while ensuring the platform complies with enterprise-level security, governance, and data privacy policies.

Key Responsibilities

• Infrastructure Architecture & Management: Lead the deployment, bare-metal configuration, maintenance, and optimization of our on-premises HPC cluster and multi-GPU architecture.
• Platform Enablement: Manage the end-to-end AI software stack, including Linux OS environments, specialized GPU drivers, runtime libraries (CUDA, NCCL), and containerization platforms.
• Developer Sandbox Orchestration: Implement and maintain workload scheduling and orchestration systems (e.g., Kubernetes, Slurm, or equivalent enterprise platforms) to manage cluster resource allocation and job prioritization for engineering teams.
• Monitoring & Performance Tuning: Establish automated telemetry and monitoring dashboards to track hardware utilization, thermal limits, and memory bandwidth, ensuring maximum compute efficiency.
• Security & Governance Compliance: Operationalize strict data-at-rest and data-in-transit security baselines, ensuring the compute environment aligns with corporate Zero Trust network architecture and compliance mandates.
• Vendor Relations & Support: Act as the primary technical interface for high-end hardware vendors and system integrators to manage system updates and platform maintenance.

Professional Qualifications

• Experience: 3+ years of dedicated systems administration experience managing Linux-based High-Performance Computing (HPC) environments or enterprise-scale GPU infrastructure.
• Technical Fluency: Hands-on experience configuring and maintaining modern enterprise GPU hardware (such as NVIDIA Ampere or Hopper architecture) in a data center context.
• Software & Tooling Mastery: Deep expertise in Linux system engineering, container technologies (Docker, Apptainer/Singularity), and cluster resource management.
• Networking & Storage: Solid baseline knowledge of high-throughput networking fabrics (e.g., InfiniBand/RoCE) and parallel or distributed enterprise storage systems.
• Education: Bachelor’s degree in computer science, Computer Engineering, System Administration, or equivalent practical industry experience.

Preferred Attributes

• Relevant professional certifications in enterprise AI infrastructure, virtualization, or cloud/hybrid architecture solutions.
• Familiarity with the infrastructure requirements supporting modern AI frameworks, machine learning lifecycles, or Large Language Model (LLM) fine-tuning pipelines.

What We Offer

• Direct access to cutting-edge, top-tier enterprise compute infrastructure.
• A collaborative environment with highly defined responsibilities and strategic, top-down execution support.
• Competitive salary, comprehensive benefits package, and professional development suppport.