Senior HPC AI Engineer

Job Title

Senior HPC AI Engineer

Role Summary

Join the Hardware Infrastructure EDA Compute team to optimize, scale, and support job scheduling and GPU-accelerated compute environments used for EDA and other compute-intensive workloads. The role focuses on scheduler engineering, automation, CI/CD, observability, and operational reliability across multi-site infrastructure.

Experience Level

Senior-level. The posting requests a minimum of 5+ years of experience operating and supporting large-scale Linux-based compute infrastructure.

Responsibilities

Key responsibilities include operating and improving scheduling and compute infrastructure, analyzing performance, and delivering automation and tooling to increase reliability and efficiency.

• Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) across a large multi-site environment supporting EDA and compute workloads.
• Analyze scheduler and infrastructure performance data to identify bottlenecks and drive improvements in utilization, throughput, and turnaround time.
• Build and improve the GPU-accelerated computing ecosystem and related tooling.
• Define and develop automation scripts, wrapper tools, CI/CD pipelines, and Infrastructure as Code for the IC design environment.
• Identify recurring operational challenges and implement automation or process changes to reduce manual effort and prevent repeat incidents.
• Perform root cause analysis and recommend corrective actions for operational issues at scale.
• Partner with customer teams to clarify requirements, evaluate trade-offs, and drive issues to closure.

Requirements

Must-have technical skills and experience needed to perform the role.

• Minimum 5+ years operating and supporting large-scale Linux-based compute infrastructure.
• Hands-on experience supporting and tuning job scheduling systems (LSF, Slurm) in HPC or silicon design environments.
• Proficiency in Linux systems administration (CentOS/RHEL).
• Proficient in modern CI/CD practices, GitOps, and Infrastructure as Code (IaC).
• Proficient in Python programming and bash scripting.
• Experience developing, fine-tuning, and deploying advanced LLM-based solutions for practical applications (e.g., NLP, chatbots, data analysis).
• Strong troubleshooting, performance analysis, and incident remediation skills.
• Experience with GPU-accelerated compute environments.

Nice-to-have:

• Deep knowledge of scheduler internals, configuration tuning, and advanced troubleshooting techniques.
• Experience with network license management (e.g., FLEXlm) automation and troubleshooting.
• Experience implementing reliability engineering practices in HPC scheduling environments.
• Experience building or enhancing observability systems (metrics, monitoring pipelines, alerting, dashboards).
• Background with container technologies used in HPC (Docker, Singularity, Podman).

Education Requirements

Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. The posting explicitly allows equivalent experience in lieu of a degree.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.