NVIDIA is looking for an exceptional engineer to grow and thrive alongside our HPC Infrastructure team that designs, evaluates, and optimizes the compute inrastructure powering NVIDIA's next-generation silicon design and AI

workloads. You will be the primary architecture reviewer and performance champion for new data center clusters being built across multiple sites globally.

What you'll be doing:

• In this position, you will own the build-out and day-to-day operation of NVIDIA's VLSI high-performance compute environments in the public cloud, and the repeatable patterns that let us stand up the next environment faster than the last.
• Bring up and operate large compute clusters on Google Cloud end to end - instance provisioning, machine images, OS pipelines, networking, identity and quota management.
• Build the automation that makes cluster bring-up reproducible: infrastructure-as-code, configuration management, image build pipelines, and host lifecycle automation including hostname and identity preservation across maintenance events.
• Extend the same patterns to new on-premises data centers so cloud and on-prem run on one toolchain rather than two, and work with networking and storage teams on cross-site connectivity, latency budgets, and what is cross-mounted versus kept site-local.
• This is a hands-on technical role. You will debug at depth when clusters misbehave - image and boot issues, mount failures, scheduler-host interactions, capacity and quota problems - and partner with the scheduling and operations engineers so what you build is operable by the whole team, not only by you.

What we need to see:

• B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or equivalent experience.
• 8+ years in infrastructure engineering, with substantial time running production compute at scale.
• Deep, hands-on expertise with a major public cloud, Google Cloud preferred - compute, networking, IAM, storage, quotas, and the operational realities of running thousands of instances rather than tens.
• Strong infrastructure-as-code and configuration management skills (Terraform, Ansible, Puppet, or equivalent), plus experience with machine image build and OS lifecycle pipelines for large fleets.
• Solid Linux systems administration and troubleshooting: filesystems, NFS mounts and latency, networking, boot and image pipelines.
• Working understanding of data center and network fundamentals for compute-intensive workloads - topology, bandwidth and latency characterisation, and the practical limits of cross-site operation - along with familiarity with batch schedulers (LSF, Slurm, or equivalent) and how compute nodes join, leave and are managed within them.
• Strong Python automation, experience bringing a new environment, cluster or data center online end to end, and the ability to work effectively across time zones. Semiconductor/EDA exposure is a plus, not a requirement.