HPC & GPU Infrastructure Engineer
US$150,000 – US$220,000 / yr base salary
Posted 6 Oct 2026
Advertised as “Senior HPC & GPU Infrastructure Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$150,000 – US$220,000 / yr |
|---|
Field of studyComputer Engineering, Computer Science, Electrical Engineering (or related)
Study levelBachelor's or higher
Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. Backed by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.
About the role
We are seeking a Senior HPC & GPU Infrastructure Engineer to take full ownership of the health, reliability, and performance of our GPU compute cluster. You will be the primary custodian of our high-density accelerator environment and the linchpin between hardware operations, distributed systems, and machine learning workflows. This role spans everything from hands-on Linux systems engineering and GPU driver bring-up to maintaining the ML software stack (CUDA/ROCm, PyTorch, JAX, vLLM). If you love squeezing every bit of performance out of hardware, enjoy debugging GPUs at scale, and want to build world-class AI infrastructure, this role is for you.
What you'll do
1. System Health & Reliability (SRE)
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On-Call Response: Act as the primary responder for system outages, GPU failures, node crashes, and cluster-wide incidents. Minimize downtime by resolving issues rapidly.
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Cluster Monitoring: Implement and maintain monitoring for GPU health, thermal behavior, PCIe/NVLink topology issues, memory errors, and overall system load.
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Vendor Liaison: Coordinate with data center staff, hardware vendors, and on-site technicians for repairs, RMA processing, and physical maintenance of the cluster.
2. Linux & Network Administration
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OS Management: Install, patch, and maintain Linux distributions (Ubuntu / CentOS / RHEL). Ensure consistent configuration, kernel tuning, and automation for large node fleets.
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Security & Access Controls: Configure VPNs, iptables/firewalls, SSH hardening, and network routing to secure our computer infrastructure.
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Identity & Storage Management: Manage LDAP/FreeIPA/AD for user identity, and administer distributed file systems such as NFS, GPFS, or Lustre.
3. GPU & ML Stack Engineering
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Deployment & Bring-Up: Lead deployment of new GPU nodes, including BIOS configuration, NUMA tuning, GPU topology validation, and cluster integration.