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AI & HPC Infrastructure Engineer

$150k - $170k

Franklin Fitch

Senior AI & HPC Infrastructure Engineer Remote (US) | $150,000 - $170,000 Base + Bonus

Submit your CV and any additional required information after you have read this description by clicking on the application button.

Our client is a highly respected global consulting and research organization that supports leading commercial enterprises, public sector institutions, and professional services firms. As part of a significant investment in AI infrastructure, they are expanding their internal high performance computing (HPC) and GPU capabilities to support next-generation machine learning and large language model (LLM) initiatives.

This is an exciting opportunity to join a small, highly skilled infrastructure team at a pivotal stage of growth. The successful candidate will play a key role in scaling a GPU environment from 8 to 32 NVIDIA H200 GPUs while helping shape the organization's long-term AI and HPC strategy.

The role is heavily project-focused, with approximately 85% dedicated to engineering, architecture, and platform development activities, and a smaller proportion supporting operational needs.

The Opportunity

You'll work at the intersection of traditional HPC, research computing, and modern AI infrastructure, supporting both analytical workloads and large-scale model training environments.

Key responsibilities include:

  • Designing, deploying, and maintaining GPU-accelerated computing infrastructure
  • Supporting large-scale AI/ML and LLM training environments
  • Managing Linux-based HPC clusters and associated services
  • Administering and optimizing parallel file systems, particularly IBM Spectrum Scale (GPFS)
  • Managing NVIDIA GPU platforms, CUDA, cuDNN, NCCL, and related tooling
  • Supporting resource scheduling through SLURM and related technologies
  • Performance tuning for distributed and multi-GPU workloads
  • Building automation, monitoring, reporting, and operational tooling
  • Collaborating with researchers, data scientists, and technical stakeholders to translate business requirements into infrastructure solutions
  • Evaluating emerging AI infrastructure technologies and recommending future platform enhancements

Required Experience

We're particularly interested in candidates who combine deep infrastructure expertise with an understanding of how end-users consume HPC resources.

Essential Skills

  • Strong Linux systems administration background
  • Experience supporting HPC or research computing environments
  • Hands-on NVIDIA GPU infrastructure experience
  • Strong experience with GPFS / IBM Spectrum Scale
  • Familiarity with job schedulers such as SLURM, LSF, or similar
  • Experience supporting distributed compute environments
  • Ability to lead projects independently with minimal oversight
  • Strong troubleshooting experience across compute, storage, networking, and hardware layers
  • Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders

Highly Desirable

  • Experience supporting AI/ML infrastructure or LLM platforms
  • Kubernetes and container orchestration experience
  • MLOps tooling exposure (MLflow, Kubeflow, etc.)
  • Experience tuning large model training and inference workloads
  • Bright Cluster Manager
  • Ansible
  • Docker, Apptainer, or Singularity
  • SAS platform experience alongside GPU/HPC expertise

Ideal Background

This role is particularly well suited to someone who:

  • Has approximately 5-10 years of relevant infrastructure experience
  • Is currently operating at a strong mid-level and ready for a senior step forward
  • Can own and deliver significant technical projects independently
  • Comes from an HPC, research computing, higher education, government, scientific computing, or technical enterprise environment
  • Enjoys balancing infrastructure engineering with emerging AI technologies

Team & Culture

You'll join a close-knit team of experienced infrastructure specialists covering HPC operations, automation, applications, and platform engineering. The group operates in a highly collaborative remote-first model, with team members distributed across the United States. xhyhwjd

A notable area of planned growth is AI and LLM infrastructure expertise, making this a high-visibility hire with significant opportunity for progression and influence.

If you're an HPC infrastructure engineer looking to move into a highly visible AI-focused environment while remaining close to the hardware, architecture, and platform engineering side of the stack, we'd love to hear from you.

Vacancy posted 12 hours ago
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