I logo

Member of Technical Staff, Cluster Administration

InferactSan Francisco, California

$200,000 - $400,000 / year

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.1

Reclaim your time by letting our AI handle the grunt work of job searching.

We continuously scan millions of openings to find your top matches.

pay-wall

Overview

Schedule
Full-time
Career level
Senior-level
Remote
Option for remote
Compensation
$200,000-$400,000/year
Benefits
Health Insurance
Dental Insurance
Vision Insurance

Job Description

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—a position that took years to build.

About the Role

We're looking for a hands-on cluster administration engineer to own and operate the high-performance GPU compute infrastructure that keeps Inferact engineering productive. Inferact runs on expensive, high-performance GPU and HPC clusters across neo-cloud and dedicated compute providers. Your job is to make sure that infrastructure is healthy, available, observable, and usable around the clock.

You'll take ownership of cluster health, GPU availability, monitoring, alerting, scheduling, access, diagnostics, and incident response across the systems our engineers rely on every day. You'll work closely with engineering leadership and infrastructure owners to standardize how we provision, operate, debug, and scale compute across providers. Your work will directly impact how fast Inferact can build, test, and improve the systems powering vLLM.

Skills and Qualifications

Minimum 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.

Preferred qualifications:

  • 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.

Bonus points if you have:

  • 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.

  • Standardized provisioning, diagnostics, monitoring, and operating patterns across multiple compute providers.

  • Carried real operational responsibility for infrastructure used by many engineers or researchers.

Logistics

  • Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.

  • Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.

  • Visa sponsorship: We sponsor visas on a case-by-case basis.

  • Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.

pay-wall

FAQs About Member of Technical Staff, Cluster Administration Jobs at Inferact

What is the work location for this position at Inferact?
This job at Inferact is located in San Francisco, California, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Inferact?
Candidates can expect a pay range of $200,000 and $400,000 per year.
What employment applies to this position at Inferact?
Inferact lists this role as a Full-time position.
What experience level is required for this role at Inferact?
Inferact is looking for a candidate with "Senior-level" experience level.
Does Inferact allow remote work for this role?
Yes, this position at Inferact supports remote work, giving candidates the flexibility to work outside the primary office location.
What benefits are offered by Inferact for this role?
Inferact offers following benefits: Health Insurance, Dental Insurance, Vision Insurance, and 401k Matching/Retirement Savings for this position. Actual benefits may vary depending on the employer's policies and employment terms.
What is the process to apply for this position at Inferact?
You can apply for this role at Inferact either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.