Member of Technical Staff, Supercomputing Infrastructure

The role

You will own and operate high-performance compute infrastructure including GPU and HPC clusters. You will ensure infrastructure is healthy, available, observable, and usable across NVIDIA GPUs, AMD GPUs, and Google TPUs.

What you will do

• Own cluster health, accelerator availability, monitoring, alerting, scheduling, access, diagnostics, and incident response.
• Standardize how to provision, operate, debug, and scale compute across providers and hardware platforms.
• Own urgent infrastructure incidents end-to-end when compute issues block engineering teams.
• Automate operational workflows.

Required qualifications

• Bachelor's degree or equivalent experience in computer science, engineering, systems administration, or similar.
• Hands-on experience administering large compute clusters, HPC environments, university or research clusters, supercomputing systems, or production GPU clusters.
• Strong Linux systems administration fundamentals across networking, processes, storage, package management, shell scripting, logs, access control, and system debugging.
• Experience operating GPU servers, including driver management, GPU health monitoring, node failures, memory errors, scheduler issues, and hardware diagnostics.
• Experience with cluster scheduling and resource allocation using SLURM, Kubernetes, or equivalent tooling.
• Ability to own urgent infrastructure incidents end-to-end when compute issues are blocking engineering teams.
• Ability to automate operational workflows using Bash, Python, Ansible, Terraform, Helm, or similar tooling.

Nice to have

• Experience managing 1,000+ GPUs in production.
• Experience operating GPU compute across providers such as Lambda, CoreWeave, Crusoe, Nebius, Together, Fireworks, RunPod, or similar environments.
• Experience improving cluster utilization, reducing idle or unavailable GPU capacity, and debugging scheduling or resource contention issues.
• Familiarity with high-performance GPU networking such as InfiniBand, RoCE, NVLink / NVSwitch, RDMA, NCCL, or equivalent systems.
• Experience with storage for HPC or ML workloads, including NFS, Lustre, Ceph, distributed filesystems, or other high-throughput storage systems.
• Experience managing secure access, identity, permissions, SSH, VPNs, bastion hosts, secrets, and basic infrastructure security hygiene.
• Background in research computing, scientific computing, ML infrastructure, SRE, platform engineering, or infrastructure operations for engineering-heavy teams.
• Managed GPU or HPC infrastructure in a university lab, national lab, research institution, AI infrastructure company, hedge fund, HFT firm, or large-scale ML platform team.
• Built monitoring, alerting, runbooks, health checks, or remediation workflows that materially reduced operational toil or incident resolution time.
• Operated Kubernetes clusters for ML or GPU workloads at meaningful scale.

Benefits

• medical, dental, and vision coverage

Before you apply

• We sponsor visas on a case-by-case basis.

About the company

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware.