S

Sciforium

Serverless AI inference platform

GPU Cluster Engineer - Hardware Operations

System AdministrationConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Three or more years of experience in Linux systems administration, including knowledge of boot processes, systemd, and disk management.
  • Strong background troubleshooting server hardware in high-density environments, including power, cooling, and PCIe topologies.
  • Experience managing networking security, including VPNs, iptables or firewalld, and VLANs, and directory services, including LDAP, FreeIPA, or Active Directory.
  • Proficiency in Bash scripting for system automation.

Responsibilities

  • Serve as the primary contact for physical system outages, hardware failures, and network interruptions to minimize downtime.
  • Monitor hardware health, including GPU thermals, power draw, and physical system loads, and identify anomalies before they affect workloads.
  • Coordinate RMA processes, physical repairs, part replacements, and routine maintenance with data center facility staff and third-party hardware vendors.
  • Rack, cable, and lead the physical bring-up of new GPU nodes, integrating power and network connectivity into the existing cluster.
  • Install, patch, and maintain Linux operating systems, including Ubuntu, CentOS, and RHEL, across bare-metal cluster servers.
  • Configure and maintain edge and internal networking, including firewalls, VPNs, and SSH access controls.
  • Administer LDAP or Active Directory for centralized user authentication and ensure network storage systems, including NFS, GPFS, and Lustre, are mounted and permissioned.

Desired Qualifications

  • Experience using configuration management tools such as Ansible, SaltStack, or Terraform for OS provisioning.
  • Familiarity with data center operations and cooling requirements for high-TDP accelerators such as NVIDIA B200 or AMD MI355x.

About the Company

Sciforium

Serverless AI inference platform

Sciforium builds an AI infrastructure stack that makes large-scale AI cheaper and easier to deploy. It offers a serverless AI inference platform that exposes access to a mix of open-source and proprietary models through a single API, running on Sciforium’s own optimized AMD hardware. By owning the hardware, platform, and models, the company provides lower costs, faster performance, and better data privacy than shared-cloud setups. Its goal is to simplify and accelerate production-ready AI deployment while reducing costs and complexity for large-scale multimodal models, and it is exploring byte-native foundation models to improve efficiency.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2024

Recently Posted Jobs

Explore more opportunities at Sciforium

See more jobs