10 days ago
Base Salary
$176k - $334k/yr
Responsibilities
- Design, implement, and maintain large-scale HPC and AI clusters with monitoring, logging, and alerting.
- Manage Linux job scheduling, workload scheduling, and orchestration tools.
- Develop and maintain continuous integration and delivery pipelines.
- Automate deployment and management of large-scale infrastructure environments and enable self-service resource consumption.
- Deploy monitoring solutions for servers, networks, and storage.
- Troubleshoot systems from bare metal and operating-system layers through software stacks and applications.
- Develop and document standard methodologies for internal teams.
- Support research and development activities and participate in proofs of concept and proofs of value.
Requirements
- Degree in Computer Science, Engineering, or a related field, or equivalent experience, plus 8 or more years of experience.
- Knowledge of HPC and AI solution technologies spanning CPUs, GPUs, high-speed interconnects, and supporting software.
- Experience with workload scheduling and orchestration tools such as Slurm and Kubernetes.
- Strong knowledge of Windows, Linux, Red Hat/CentOS, Ubuntu, networking, operating-system internals, ACLs, security protections, TCP, DHCP, DNS, and related tools.
- Experience with storage solutions such as Lustre, GPFS, and Weka.io, plus familiarity with emerging storage technologies.
- Python programming and Bash scripting experience.
- Experience with automation and configuration-management tools such as Jenkins, Ansible, Puppet, and Chef.
- Deep knowledge of InfiniBand and Ethernet networking protocols.
- Deep understanding of virtual systems such as VMware, Hyper-V, KVM, or Citrix.
- Familiarity with AWS, Azure, or Google Cloud.
- Preferred qualifications include CPU or GPU architecture knowledge, Kubernetes and container technologies, GPU-focused platforms such as DGX and CUDA, and RDMA fabrics using InfiniBand or RoCE.
Benefits
- Competitive salary, equity, and benefits package.
- Base salary varies by location, experience, and other objective job-related factors.
- Applications will be accepted at least until November 3, 2026.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.