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Slurm Jobs (NOW HIRING)

TensorWave

Staff Database Engineer

Las Vegas, NV · Remote

Slurm, NetBox, and Infrastructure Data Systems * Serve as the senior database engineering owner for infrastructure-adjacent database platforms, including Slurm and NetBox. * For Slurm environments ...

Cynet Systems

HPC Consultant

Fremont, CA · On-site

$52 - $57/hr

Strong expertise in SLURM configuration, tuning, and troubleshooting. * Strong knowledge of Linux operating systems. * Experience with HPC storage systems and I/O performance analysis. * Experience ...

Nvidia

Senior HPC and LSF Operations Engineer

Westford, MA · Hybrid

$108K - $148K/yr

Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads * Analyze scheduler and ...

Jahnel Group

HPC Administrator

Schenectady, NY · On-site

Administer and maintain Altair Access , PBS Professional , and Slurm workload scheduling environments * Manage user onboarding, account provisioning, queue access, and resource allocation policies

Nvidia

Senior HPC and LSF Operations Engineer

Durham, NC · Hybrid

$101K - $138K/yr

Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads * Analyze scheduler and ...

Prior Labs

Senior ML Infrastructure Engineer

New York, NY · On-site

$118K - $161K/yr

Today we run Slurm on GCP across multiple clusters. We're scaling to multi-cluster, multi-provider infrastructure and evaluating new hardware generations as they come online. You own the full stack ...

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Slurm information

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$106.4K

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How much do slurm jobs pay per year?

As of Jul 8, 2026, the average yearly pay for slurm in the United States is $106,432.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $205,000.00 per year, depending on experience, location, and employer.

How to see Slurm jobs?

To see Slurm jobs, use the command 'squeue' to display queued and running jobs, or 'sacct' for accounting information on completed jobs. These commands help system administrators and users monitor job status in a high-performance computing environment. Proper permissions and environment modules are often required to access job details.

How many jobs can Slurm handle?

Slurm is a workload manager used in high-performance computing environments, capable of handling thousands to hundreds of thousands of jobs simultaneously depending on the system's hardware and configuration. Its scalability allows efficient scheduling and management of large job queues in supercomputing clusters. Proper system tuning and resource allocation are essential for optimal performance when managing large job volumes.

Is Slurm still used?

Slurm is a widely used open-source workload manager for high-performance computing clusters. It is actively maintained and commonly employed in research, scientific, and enterprise environments to schedule and manage jobs efficiently.

What is a Slurm job?

A Slurm job refers to a task or set of tasks submitted to a Slurm workload manager, which schedules and manages compute jobs on high-performance computing clusters. Users submit jobs with specific resource requirements, and Slurm handles job queuing, execution, and monitoring. Knowledge of command-line tools and job scripting is essential for managing Slurm jobs effectively.
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Slurm jobs near you
Infographic showing various Slurm job openings in the United States as of July 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $106,432 per year, or $51.2 per hour.
Senior Software Engineer, Cloud-Native Stack - CSP Engagements

Senior Software Engineer, Cloud-Native Stack - CSP Engagements

NVIDIA Corporation

Santa Clara, CA • On-site

Other

Re-posted 11 days ago

Job description

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team.
What you'll be doing:
  • Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc.
  • Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities.
  • Drive joint architecture reviews and whiteboard" sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests.
  • Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites.
  • Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG.
  • Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation.
What we need to see:
  • Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins).
  • Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters.
  • Proven track record debugging large-scale, cloud-native stacks across networking (RDMA/RoCE), storage, and control planes.
  • Customer-facing engineering or solutions-architect background: requirements gathering, PoC ownership, roadmap influence.
  • Familiarity with CI/CD (GitHub Actions, Tekton), observability (Prometheus, OpenTelemetry), and infrastructure-as-code.
  • Excellent communication-able to switch between deep technical detail and high-level business impact.
  • 10+ years of professional software development experience in distributed systems (Go, Rust, C/C++ or Python for tooling).
  • BS or MS (or equivalent experience) in Computer Engineering, Computer Science, or related field.
Ways to stand out from the crowd:
  • Upstream contributions to Kubernetes, Slurm, Volcano, or similar projects.
  • Experience with GPU computing (CUDA), deep learning workloads
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until July 6, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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