AI and ML HPC Cluster Engineer, AI and ML HPC Cluster Engineer

NVIDIA; Colorado; On-site; USD 124,000 - 195,500; Full time

Job summary

A leading technology company located in Colorado is seeking to fill a critical role in managing AI superclusters. The successful candidate will support day-to-day operations of both on-premises and multi-cloud AI/HPC clusters, ensuring optimal performance and user satisfaction. The role requires a Bachelor's degree and at least 2 years of experience with compute infrastructure and AI job schedulers. The base salary ranges from 124,000 to 195,500 USD, accompanied by equity and benefits. Applications accepted until February 24, 2026.

Qualifications

• Minimum 2+ years of experience administering multi-node compute infrastructure.
• Background in managing AI/HPC job schedulers.
• Proficient in Centos/RHEL and/or Ubuntu Linux distributions.

Responsibilities

• Support day-to-day operations of AI/HPC clusters.
• Directly administer internal research clusters.
• Develop and improve the ecosystem around GPU-accelerated computing.

Skills

Administration of multi-node compute infrastructure

Working with AI/HPC job schedulers

Proficient in Centos/RHEL, Ubuntu

Cluster configuration management tools

Container technologies

Python programming

Bash scripting

Education

Bachelor’s degree in Computer Science, Electrical Engineering or related field

Tools

Ansible

Docker

Kubernetes

Job description

NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Superclusters (MARS) builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads.

What You\'ll Be Doing

• Support day-to-day operations of production on-premises and multi-cloud AI/HPC clusters, ensuring system health, user satisfaction, and efficient resource utilization.
• Directly administer internal research clusters, conduct upgrades, incident response, and reliability improvements.
• Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions.
• Maintain heterogeneous AI/ML clusters on-premises and in the cloud.
• Support our researchers to run their workloads including performance analysis and optimizations
• Analyze and optimize cluster efficiency, job fragmentation, and GPU waste to meet internal SLA targets.
• Support root cause analysis and suggest corrective action. Proactively find and fix issues before they occur.
• Triage and support postmortems for reliability incidents affecting users or infrastructure.
• Participate in a shared on-call rotation supported by strong automation, clear paths for responding to critical issues, and well-defined incident workflows.

What We Need To See

• Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience
• Minimum 2+ years of experience administering multi-node compute infrastructure
• Background in managing AI/HPC job schedulers like Slurm, K8s, PBS, RTDA, BCM (formerly known as Bright), or LSF
• Proficient in administering Centos/RHEL and/or Ubuntu Linux distributions
• Proven understanding of cluster configuration management tools (Ansible, Puppet, Salt, etc.), container technologies (Docker, Singularity, Podman, Shifter, Charliecloud), Python programming, and bash scripting.
• Passion for continual learning and staying ahead of emerging technologies and effective approaches in the HPC and AI/ML infrastructure fields.

Ways To Stand Out From The Crowd

• Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking
• Experience with AI/ML concepts, algorithms, models, and frameworks (PyTorch, Tensorflow)
• Experience with InfiniBand with IBOP and RDMA
• Understanding of fast, distributed storage systems such as Lustre and GPFS for AI/HPC workloads
• Applied knowledge in AI/HPC workflows that involve MPI

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 24, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.