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Lockheed Martin Corporation United States $73k - $188k/yr
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Why this grade This listing scored 48/100, which is a D. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Freshness 8 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
-5 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
What you’ll be doing:
- 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.
What we need to see:
- 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 from the crowd:
- 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.
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hard-working people on the planet working for us. If you're creative, hard-working and self-motivated, 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 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 September 7, 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.Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 05 Sep 2026 Himalayas first sighting
Seen on 1 board over 0 days.