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Slurm Jobs (NOW HIRING)

Summa

HPC Platform Engineer

Houston, TX · Hybrid

$70 - $90/hr

Configure and tune job schedulers (Slurm preferred) * Support distributed multi-node workloads (MPI) * Install, upgrade, and maintain HPC infrastructure * Configure and optimize parallel file systems ...

VTG

High-Performance Computing Engineer

Mclean, VA

Experience with NVidia, Cray, managing clusters, Slurm, Linux, CUDA, high-speed networks as well as an understanding of the customer's A&A process. Qualifications: * Active Top Secret/Sensitive ...

Biohub

Staff AI Infrastructure Engineer

Redwood City, CA · On-site +1

$131K - $172K/yr

Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the ...

Spellbrush

HPC/ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

You'll serve as the bridge between our researchers and the bare GPU machines, helping to make sure that SLURM jobs are running, parallel filesystems are serving, network is transmitting, and that the ...

Spellbrush

HPC/ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

You'll serve as the bridge between our researchers and the bare GPU machines, helping to make sure that SLURM jobs are running, parallel filesystems are serving, network is transmitting, and that the ...

TensorWave

Staff Database Engineer

Las Vegas, NV · On-site

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 ...

Uw

Research Scientist/Engineer 1

Seattle, WA · On-site

$70K/yr

Slurm job submission, resource requests, and environment management. Desired Requirements: 1. Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein integration. 2. GPU experience:

TensorWave

Staff Database Engineer

Las Vegas, NV · On-site +1

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

Tualatin, OR · 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 ...

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Slurm information

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$11K

$106.4K

$212.5K

How much do slurm jobs pay per year?

As of Jul 7, 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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What cities are hiring for Slurm jobs? Cities with the most Slurm job openings:
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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.
Member of Technical Staff (AI Infrastructure Engineer)

Member of Technical Staff (AI Infrastructure Engineer)

Perplexity

San Francisco, CA • On-site

$220K - $405K/yr

Full-time

Re-posted 16 days ago

Job description

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters
Responsibilities
  • Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads
  • Manage and optimize Slurm-based HPC environments for distributed training of large language models
  • Develop robust APIs and orchestration systems for both training pipelines and inference services
  • Implement resource scheduling and job management systems across heterogeneous compute environments
  • Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure
  • Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm
  • Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services
  • Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands
Qualifications
  • Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management
  • Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization
  • Experience with deploying and managing distributed training systems at scale
  • Deep understanding of container orchestration and distributed systems architecture
  • High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies)
  • Experience managing GPU clusters and optimizing compute resource utilization
Required Skills
  • Expert-level Kubernetes administration and YAML configuration management
  • Proficiency with Slurm job scheduling, resource management, and cluster configuration
  • Python and C++ programming with focus on systems and infrastructure automation
  • Hands-on experience with ML frameworks such as PyTorch in distributed training contexts
  • Strong understanding of networking, storage, and compute resource management for ML workloads
  • Experience developing APIs and managing distributed systems for both batch and real-time workloads
  • Solid debugging and monitoring skills with expertise in observability tools for containerized environments
Preferred Skills
  • Experience with Kubernetes operators and custom controllers for ML workloads
  • Advanced Slurm administration including multi-cluster federation and advanced scheduling policies
  • Familiarity with GPU cluster management and CUDA optimization
  • Experience with other ML frameworks like TensorFlow or distributed training libraries
  • Background in HPC environments, parallel computing, and high-performance networking
  • Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices
  • Experience with container registries, image optimization, and multi-stage builds for ML workloads
Required Experience
  • Demonstrated experience managing large-scale Kubernetes deployments in production environments
  • Proven track record with Slurm cluster administration and HPC workload management
  • Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure
  • Experience supporting both long-running training jobs and high-availability inference services
  • Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management

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