Support datacenter lifecycle programs — expansions, technology refreshes, and site exits — by mapping workload placement, identifying required data, and minimizing data replication scope
Define storage policies and best practices — data lifecycle, tiering strategies, snapshot/clone workflows (e.g., FlexClone for EDA workspace branching), and capacity planning recommendations
Collaborate with IT, EDA tool teams, EDA operations, and networking to translate workload requirements into storage architecture guidance
Investigate storage-related issues affecting production workloads — characterize the impact, identify causes, and recommend preventive measures or design changes
Contribute to NVIDIA’s storage strategy and roadmap for next-generation compute, AI workloads, and cloud-hybrid infrastructure
What we need to see
Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience)
8+ years of experience with large-scale NFS and networked storage systems in Linux environments
Hands-on experience with at least one enterprise or HPC storage platform (NetApp, VAST, Pure, Lustre, GPFS, Ceph, Weka)
Strong Linux systems skills and storage performance analysis — ability to characterize how storage behavior affects workload outcomes
Proficient in Python and Bash scripting for automation and tooling
Experience with cloud-based storage solutions (GCP Filestore, NetApp Cloud Volumes, AWS FSx, or similar)
Experience with observability and metrics collection systems — building or leveraging dashboards, telemetry pipelines, and alerting to monitor storage health and performance (e.g., Prometheus, Grafana, Netdata, or similar)
Ways to stand out from the crowd
Experience with EDA infrastructure or semiconductor design workflows and their unique storage I/O patterns
Familiarity with enterprise storage features such as instant clones, snapshots, caching tiers, and data tiering policies (e.g., NetApp FlexClone/FlexCache or equivalent)
Experience correlating infrastructure telemetry with workload performance — e.g., tying storage metrics to job scheduler data (LSF, Slurm)
Background in datacenter migration planning, capacity modeling, or data placement strategy at multi-petabyte scale
Experience with container technologies (Docker, Enroot)
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s an outstanding legacy of innovation that’s motivated by great technology—and outstanding people. Widely considered to be one of the technology world’s most desirable employers, NVIDIA is an industry leader with groundbreaking developments in High-Performance Computing, Artificial Intelligence and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery and powers what were once science fiction inventions from artificial intelligence to autonomous cars.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 20, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
