Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Go @ 7
Kubernetes @ 4
Linux @ 4
Terraform @ 4
Python @ 7
ArgoCD @ 4
Distributed Systems @ 4
Communication @ 4
Networking @ 4
Debugging @ 4
API @ 4
GPU @ 4
Observability @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling, and operational systems that make GPU clusters reliable, scalable, and safe to run. This role is part of a production engineering team focused on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments.
Responsibilities
- Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments.
- Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations.
- Improve Day 0 / Day 1 / Day 2 workflows for cluster bringup, handoff, and production operations.
- Reduce manual production touches through APIs, GitOps, automation, and agent-assisted workflows.
- Participate in on-call, incident response, debugging, and durable follow-up work.
- Partner with platform, storage, networking, security, and workload teams to make infrastructure production-ready.
Requirements
- 8+ years of experience building or operating production infrastructure.
- Strong programming skills in Python, Go, or similar.
- Experience with Linux, Kubernetes, containers, cloud infrastructure, or infrastructure automation.
- Ability to troubleshoot distributed systems in production.
- Clear communication and ability to work across teams.
- BS/MS in Computer Science or equivalent experience.
Ways to stand out
- Experience with GPU infrastructure, Kubernetes operators, GitOps, Terraform, ArgoCD, or fleet automation.
- Experience with SLOs, on-call, incident response, observability, and reliability practices.
- Exposure to BMaaS, VMaaS, managed Kubernetes, or multi-cloud infrastructure.
Compensation & Other Details
- Base salary range: 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 (see NVIDIA benefits page).
- Applications for this job will be accepted at least until May 31, 2026.
- This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate on the basis of characteristics protected by law.