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Senior HPC & GPU Infrastructure Engineer

Sciforium· Engineering
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San Francisco, CA$150k - $220k + equityFull-timePosted 8mo ago

About the role

Senior role owning the health, reliability, and performance of the GPU compute cluster, spanning Linux systems, GPU driver bring-up, and ML software stack maintenance to support frontier AI models and real-time applications.

Responsibilities

  • 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.
  • Cluster Monitoring: Implement and maintain monitoring for GPU health, thermal behavior, PCIe/NVLink topology issues, memory errors, and overall system load.
  • Vendor Liaison: Coordinate with data center staff, hardware vendors, and on-site technicians for repairs, RMA processing, and physical maintenance of the cluster.
  • OS Management: Install, patch, and maintain Linux distributions (Ubuntu / CentOS / RHEL). Ensure consistent configuration, kernel tuning, and automation for large node fleets.
  • Security & Access Controls: Configure VPNs, iptables/firewalls, SSH hardening, and network routing to secure our computer infrastructure.
  • Identity & Storage Management: Manage LDAP/FreeIPA/AD for user identity, and administer distributed file systems such as NFS, GPFS, or Lustre.
  • Deployment & Bring-Up: Lead deployment of new GPU nodes, including BIOS configuration, NUMA tuning, GPU topology validation, and cluster integration.
  • Driver & Kernel Management: Build and optimize kernel modules, maintain GPU drivers and runtime stacks for both NVIDIA (CUDA) and AMD (ROCm).
  • Software Stack Maintenance: Maintain and optimize ML frameworks and libraries PyTorch, JAX, CUDA toolkit, cuDNN, ROCm, NCCL, and supporting runtime systems.
  • Advanced Debugging: Troubleshoot complex interactions involving GPUs, compilers, ML frameworks, and distributed training runtimes (e.g., vLLM compilation failures, CUDA memory leaks, ROCm kernel crashes).

Qualifications

  • 5+ years of experience in HPC, GPU cluster operations, Linux systems engineering, or similar roles.
  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.
  • Strong expertise with NVIDIA (H100/B200) or AMD (MI325x/MI355x) GPUs, including driver and kernel-level debugging.
  • Deep understanding of Linux internals, kernel modules, hardware bring-up, and systems performance tuning.
  • Experience with network security, including VPNs, iptables/firewalld, SSH, and identity management (LDAP/FreeIPA/AD).
  • Proficiency in Bash and Python for scripting, automation, and workflow tooling.
  • Familiarity with ML software stacks: CUDA toolkit, cuDNN, NCCL, ROCm, JAX/PyTorch runtime behavior.
  • Deep debugging experience with NVLink/NVSwitch fabrics and RDMA networking.

Skills

Required:GPU cluster operationsLinux systems engineeringNetworking and securityPython/Bash scriptingML stack experience

Benefits

  • Medical, dental, and vision insurance
  • 401k plan
  • Daily lunch, snacks, and beverages
  • Flexible time off
  • Competitive salary and equity
Last updated Oct 9, 2026. Interested? Apply on the company site.

About Sciforium

Byte-Native AI Models & Infrastructure

Sciforium is pioneering the future of AI infrastructure and research. We're developing byte-native multimodal foundation models while delivering serverless LLM serving at a fraction of traditional costs

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