Opportunity Software Engineering work from LinkedIn, X, Reddit and Upwork, in one list. Find me work
techroles

Member of Technical Staff, Supercomputing Infrastructure

Inferact inferact.ai Open · verified Oct 24, 2026
On-site San Francisco Full-time Senior Software Engineering

At a glance

Senior Software Engineering role at Inferact. San Francisco · full-time · $200,000–$400,000 base.

SalaryStated by Inferact
$200,000 – $400,000
Base salary for this role, in USD per year, as published in the posting.
This role, from InferactOur estimate for the market: $195,575–$250,000Median $220,500
The range includes the market median of $220,500 for senior software engineering roles in San Francisco.
Worked out from 214 postings that stated pay, median $220,500. Last updated Oct 24, 2026.
RoleSoftware Engineering
SenioritySenior
LocationSan Francisco
WorkplaceOn-site
EmploymentFull-time
Base pay$200,000–$400,000
PostedAug 21, 2026 · 2mo ago
Role brief

techroles summary, based on the employer's posting.

What you'll do

  • Keep GPU and HPC clusters healthy, available and usable across providers, from NVIDIA and AMD systems to TPU environments
  • Track accelerator health through monitoring and alerts, then diagnose node, memory, driver and scheduler failures
  • Manage cluster scheduling, compute access and incident response when infrastructure problems block engineering work
  • Set consistent ways to provision, operate, debug and scale compute across different providers and hardware
  • Automate recurring infrastructure work and improve utilization by addressing idle capacity and resource contention

What you bring

  • A computer science, engineering, systems administration or related degree, or equivalent experience
  • Hands-on administration of large compute, HPC, research or production GPU clusters
  • Strong Linux administration skills, including networking, storage, access controls, shell scripting and system debugging
  • Experience maintaining GPU servers and using SLURM, Kubernetes or comparable tools for scheduling
  • Ability to handle urgent infrastructure incidents and automate operations with Bash, Python, Ansible, Terraform, Helm or similar tools

Who this fits

This hands-on senior infrastructure role suits someone who has operated substantial compute clusters and can support engineering teams through urgent incidents. The position is based onsite in San Francisco, with US remote work considered for exceptional candidates. Visa sponsorship is considered individually.

From the employer

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 supercomputing infrastructure engineer to own and operate the high-performance compute infrastructure that keeps Inferact engineering productive. Inferact runs on expensive, high-performance GPU and HPC clusters across neo-cloud and dedicated compute providers, on heterogeneous hardware that spans NVIDIA GPUs, AMD GPUs, and Google TPUs. Your job is to make sure that infrastructure is healthy, available, observable, and usable around the clock.

You'll take ownership of cluster health, accelerator availability, monitoring, alerting, scheduling, access, diagnostics, and incident response across the systems our engineers rely on every day, from NVIDIA and AMD GPU clusters to TPU environments. You'll work closely with engineering leadership and infrastructure owners to standardize how we provision, operate, debug, and scale compute across providers and hardware platforms. 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 managing 1,000+ GPGPUs 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.

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.

Opportunity

Software Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Software Engineering$200k+

Find me work

By the team behind techroles.

Find me work
Opportunity

Software Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind techroles.