Full-Time

GPU Cluster Engineer

Hardware Operations

Sciforium

Sciforium

11-50 employees

Serverless AI inference platform

Compensation Overview

$150k - $180k/yr

San Francisco, CA, USA + 1 more

More locations: San Jose, CA, USA

In Person

Category
Hardware Engineering (1)
Required Skills
Graphics Processing Unit (GPU)
Bash
LDAP
Terraform
Ansible
SaltStack

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Requirements
  • At least 3 years of experience in Linux systems administration, including deep knowledge of boot processes, systemd, and disk management.
  • Strong server hardware troubleshooting experience in high-density environments, including power, cooling, and PCIe topologies.
  • Experience managing networking security using VPNs, iptables or firewalld, and VLANs, along with directory services such as LDAP, FreeIPA, or Active Directory.
  • Proficiency in Bash scripting for essential system automation.
Responsibilities
  • Serve as the primary point of contact for physical system outages, hardware failures, and network interruptions to minimize downtime.
  • Proactively monitor GPU thermals, power draw, physical system loads, and other hardware health indicators to detect anomalies before they affect active workloads.
  • Coordinate RMA processes, physical repairs, part replacements, and routine maintenance with data center facility staff and third-party hardware vendors.
  • Rack and cable new GPU nodes and lead their physical bring-up, 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 strict SSH access controls.
  • Administer LDAP and Active Directory for centralized user authentication.
  • Ensure network storage systems, including NFS, GPFS, and Lustre, are reliably mounted and properly permissioned.
Desired Qualifications
  • Experience using configuration management tools such as Ansible, SaltStack, or Terraform for operating-system provisioning.
  • Familiarity with data center operations and cooling requirements for high-TDP accelerators such as NVIDIA B200 or AMD MI355x.

Sciforium provides an AI infrastructure stack with a serverless inference platform, giving access to a mix of open-source and proprietary models through a single API. It runs on its own custom-optimized AMD hardware, delivering models without shared cloud servers to reduce costs, boost performance, and improve data privacy. The company differentiates itself by owning the full stack—hardware, software, and models—and by pursuing byte-native multimodal foundation models. Its goal is to simplify and speed up production-ready AI deployment while lowering costs and complexity for large-scale models.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

San Francisco, California

Founded

2024

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Simplify Jobs

Simplify's Take

What believers are saying

  • SignalFire still lists Sciforium as current, and AMD promoted it on 2026-07-15.
  • Jobs boards showed twelve openings in 2026, signaling aggressive hiring and execution.
  • Docs show a live console and API, indicating a real product beyond marketing.

What critics are saying

  • Sciforium remains tiny: Built In listed seven employees on 2026-02-18.
  • Heavy dependence on AMD and seed capital creates concentration risk if priorities shift.
  • A crowded inference market from OpenAI, Anthropic, and Databricks compresses pricing fast.

What makes Sciforium unique

  • Sciforium pairs byte-native multimodal models with a vertically integrated serving stack in 2026.
  • AMD collaboration supports custom hardware optimization, unlike generic cloud inference vendors.
  • Its serverless API unifies text, vision, image generation, and speech-to-text workloads.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Meal Benefits

Company Equity

Growth & Insights

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%