Senior HPC Cluster Engineer

NVIDIA is searching for a highly skilled HPC Cluster Engineer to design, deploy, and operate GPU Compute Clusters for Electronic Design Automation and high-performance computing workloads across multiple teams and projects. The role collaborates with researchers and infrastructure teams to ensure clusters are performant, scalable, and reliable.

• Develop and enhance our ecosystem around GPU-accelerated computing, including developing scalable automation solutions.
• Continuously improve infrastructure provisioning, management, observability, and day-to-day operation through automation.
• Provide technical leadership and strategic guidance for managing large-scale HPC systems, including deployment of compute, networking, and storage.
• Foster strong customer and multi-functional partnerships to ensure consistent cluster support and rapidly adapt to evolving user needs.
• Support researchers to run their EDA workloads, including performance analysis and optimizations.
• Conduct root cause analysis and suggest corrective action; proactively find and fix issues before they occur.
• Build innovative tooling to accelerate researchers' velocity, debugging, and software performance at scale.

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field, or equivalent experience.
• Minimum of 5 years of proven experience crafting and operating large-scale compute infrastructure, including cluster configuration management tools such as BCM or Ansible.
• Experience with AI/HPC job schedulers and orchestrators such as Slurm, LSF, PBS or K8s, and applied experience with AI/HPC workflows that use MPI and NCCL.
• Proficiency in using Linux including Rocky/Centos/RHEL and/or Ubuntu Linux distributions, with a solid understanding of container technologies such as Enroot and Docker.
• Proficiency in Python and Bash.
• Experience analyzing and tuning performance for a variety of EDA workloads, with excellent problem‑solving skills to identify bottlenecks and implement scalable solutions.
• Excellent communication and collaboration skills, with the ability to work effectively with various teams and individuals.
• Passion for continual learning and staying ahead of new technologies and effective approaches in the HPC infrastructure fields.

• Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking.
• Experience supporting EDA workloads and tools.
• Familiarity with high‑speed networking pertaining to HPC, including Infini Band, RDMA and RoCE.
• Understanding of fast, distributed storage systems such as Lustre and GPFS for AI/HPC workloads.
• Familiarity with metrics collection and visualization at scale with Prometheus, Open Search and Grafana.

The base salary will be determined based on location, experience, and the pay of employees in similar positions. Base salary ranges are $152,000 – $241,500 for Level3 and $184,000 – $287,500 for Level
4. You will also be eligible for equity and benefits.

Applications will be accepted until March
15,2026.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. We do not discriminate 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.