1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Serve as the primary architecture reviewer and performance champion for new data center clusters across global sites.
- Own the build-out and day-to-day operation of VLSI HPC environments in the public cloud.
- Provision and operate large Google Cloud compute clusters, including machine images, OS pipelines, networking, identity, and quota management.
- Build reproducible infrastructure-as-code, configuration-management, image-build, and host-lifecycle automation.
- Extend cloud infrastructure patterns to on-premises data centers using a shared toolchain.
- Partner with networking and storage teams on cross-site connectivity, latency budgets, and site-local versus cross-mounted storage.
- Debug cluster image, boot, mount, scheduler, capacity, and quota issues and collaborate with scheduling and operations engineers.
Requirements
- B.E., B.Tech, or M.Tech in Computer Science or Electrical Engineering, or equivalent experience.
- At least 8 years of infrastructure engineering experience, including substantial production compute operations at scale.
- Deep hands-on experience with a major public cloud, preferably Google Cloud, including compute, networking, IAM, storage, quotas, and large-instance-fleet operations.
- Strong infrastructure-as-code and configuration-management skills with Terraform, Ansible, Puppet, or equivalent tools.
- Experience with machine-image building and operating-system lifecycle pipelines for large fleets.
- Strong Linux systems administration and troubleshooting skills, including filesystems, NFS mounts and latency, networking, boot, and image pipelines.
- Understanding of data center and network fundamentals, including topology, bandwidth, latency characterization, and cross-site operational limits.
- Familiarity with batch schedulers such as LSF or Slurm and compute-node lifecycle management within those schedulers.
- Strong Python automation skills and experience bringing a new environment, cluster, or data center online end to end.
- Ability to work effectively across time zones; semiconductor or EDA experience is preferred but not required.
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.