HPC Operations Engineer
NVIDIA
HPC Operations Engineer
NVIDIA
Designs the chips and software that power AI
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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
As an HPC Operations Engineer at NVIDIA, you will play a pivotal role in ensuring the flawless operation of our high-performance computing (HPC) environment. This opportunity is outstanding as you will be part of a world-class team that powers semiconductor build and advanced engineering workflows. By joining us, you will help develop the future of computing while being immersed in an innovative and encouraging environment.
What you'll be doing:
Provide first-line support for HPC users across scheduling, compute, storage, and access-related issues
Troubleshoot job failures, scheduler errors, resource constraints, and performance concerns, driving issues to resolution or appropriate customer concern
Perform triage of infrastructure incidents, gathering diagnostics and advancing to subject matter experts (SMEs) when issues extend beyond defined ownership
Monitor system health, queues, node status, and service availability to ensure stable daily operations
Complete established operational procedures for maintenance, patching, and configuration updates
Develop and maintain operational documentation, runbooks, knowledge base articles, and guidelines for users and internal teams
Contribute to improving team processes by identifying recurring issues and proposing practical workflow refinements
What we need to see:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field, or equivalent experience
2+ years of experience supporting Linux-based production environments
Solid Linux systems administration fundamentals (RHEL/CentOS and/or Ubuntu)
Ability to troubleshoot technical issues methodically and determine when a customer concern requires attention
Experience interacting directly with users in a technical support or operations role
Strong written communication skills with the ability to produce clear documentation and procedural guides
Demonstrated ability to follow established processes while maintaining attention to detail
Ways to stand out from the crowd:
Foundational scripting or automation experience (e.g., Bash or Python) sufficient to support routine operational tasks
Solid understanding of workload schedulers such as LSF, Slurm, or similar systems
Strong grasp of network computing supporting infrastructure (NFS, automounter, LDAP)
Experience supporting HPC or large-scale compute environments
Familiarity with EDA workloads
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world on our team and our collaborative talent continues to drive NVIDIA's growth. We are seeking creative and independent engineers with real passion for technology!
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com
#LI-Hybrid
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
Explore more opportunities at NVIDIA