Job description

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 an inclusive, 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. What does it take to keep exabytes of AI data durable, fast, and available around the clock? Our team works on that every day for DGX Cloud, which brings NVIDIA’s accelerated computing to AI developers and researchers inside and outside the company. We run the storage platform behind it, serving the AI/ML datasets, checkpoints, and artifacts that GPU workloads access through APIs. We automate first and own the whole stack, from individual drives to API endpoints, balancing the uptime we promise users with letting developers ship changes safely. Sound like your kind of problem? What you’ll be doing: We operate large object storage deployments end to end, from the API and metadata tiers down to data placement, replication, erasure coding, and security. The work includes: Defining the SLOs we hold ourselves to for availability, latency, and durability, and using error budgets with DGX Cloud platform teams to decide when to ship. Automating the fleet lifecycle, from bare-metal provisioning and drive onboarding to rebalancing, kernel and firmware updates, and failure replacement, so routine work happens without a human. Bringing new data halls and regions into production, hundreds of petabytes at a time, with data center, network and hardware partners. Shipping storage software and configuration through CI/CD and infrastructure as code (Ansible, Kubernetes), with canary rollouts and fast rollback. Forecasting capacity with hardware and supply chain teams, and tuning performance with networking teams for AI access patterns, from multipart uploads to high-concurrency reads from GPU clusters. Delivering 24/7 operational excellence and support: sharing on-call across a global team that hands off around the clock, chasing down hard problems across the stack, and writing blameless postmortems that lead to lasting fixes. What we need to see: BS degree in Computer Science, Computer Engineering, or a related field, or equivalent experience. 8 years in SRE, production engineering, or infrastructure operations, including 3 years running distributed object storage in production at petabyte scale or larger. Deep knowledge of object storage internals, including data placement, replication and erasure coding, consistency, and failure domains, along with S3 API semantics. Strong Linux skills on bare metal across storage, networking, and performance analysis. Diagnosing hardware faults at fleet scale and working with vendors to resolve them. Python and shell for automation, plus hands-on infrastructure as code with Ansible,) Git workflows, and CI/CD. Experience building observability with Prometheus and Grafana, defining SLOs, and writing clear postmortems, runbooks, and design docs. Ways to stand out from the crowd: Operating object storage at petabyte-to-exabyte scale, open-source or cloud, or contributing to open-source storage projects. Migrating petabytes between clusters or platforms without downtime. Serving AI/ML or HPC data pipelines from object storage, such as dataset streaming and checkpointing. Building AI-assisted tooling for operations work. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you re creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 176,000 USD - 276,000 USD for Level 4, and 208,000 USD - 333,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 24, 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.

Requirements

Must-haves

We operate large object storage deployments end to end, from the API and metadata tiers down to data placement, replication, erasure coding, and security. The work includes:
Defining the SLOs we hold ourselves to for availability, latency, and durability, and using error budgets with DGX Cloud platform teams to decide when to ship.
Automating the fleet lifecycle, from bare-metal provisioning and drive onboarding to rebalancing, kernel and firmware updates, and failure replacement, so routine work happens without a human.
Bringing new data halls and regions into production, hundreds of petabytes at a time, with data center, network and hardware partners.
Shipping storage software and configuration through CI/CD and infrastructure as code (Ansible, Kubernetes), with canary rollouts and fast rollback.
Forecasting capacity with hardware and supply chain teams, and tuning performance with networking teams for AI access patterns, from multipart uploads to high-concurrency reads from GPU clusters.
BS degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
8 years in SRE, production engineering, or infrastructure operations, including 3 years running distributed object storage in production at petabyte scale or larger.
Deep knowledge of object storage internals, including data placement, replication and erasure coding, consistency, and failure domains, along with S3 API semantics.
Strong Linux skills on bare metal across storage, networking, and performance analysis.
Diagnosing hardware faults at fleet scale and working with vendors to resolve them.
Python and shell for automation, plus hands-on infrastructure as code with Ansible,) Git workflows, and CI/CD.
Experience building observability with Prometheus and Grafana, defining SLOs, and writing clear postmortems, runbooks, and design docs.
Operating object storage at petabyte-to-exabyte scale, open-source or cloud, or contributing to open-source storage projects.
Migrating petabytes between clusters or platforms without downtime.
Serving AI/ML or HPC data pipelines from object storage, such as dataset streaming and checkpointing.
Building AI-assisted tooling for operations work.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 24, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

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Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlapici/cdkubernetespython

Platform: workday
Effort: long

Benefits

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