Senior Software Engineer, Kubernetes Runtime and Release

NVIDIA Ltd.
United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$184,000 - $287,500
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Application Release Automation Cloud Computing Distributed Systems Release Management Software Engineering Verification and Validation (Software) Graphics Processing Unit (GPU) Kubernetes Information Technology Hardware Infrastructure
+1 more
Cloud Integration

Requirements

Software Engineering, Public Cloud, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Cloud Computing, Release Management/Engineering, Application Programming Interface (API), Automation, Financial Control, Software Validation, * 6+ years building production infrastructure software or distributed systems.

  • Strong programming skills in Go or another language to build production systems, with willingness to work primarily in Go.
  • Kubernetes experience and depth in at least one area: controllers and operators, release automation, test and validation systems, or cloud integration.
  • Experience delivering engineering projects, diagnosing complex failures, and collaborating across teams.
  • BS or MS in Computer Science, Engineering, or equivalent experience.

Ways to stand out from the crowd:

  • Experience in any of these areas is valuable, but not required:
  • Go development with controller-runtime, CRDs, and reconcilers.
  • Release qualification across multiple environments or platforms.
  • GPU infrastructure, accelerated networking, or GPU scheduling.
  • Bringing new hardware, regions, or cloud providers into production.
  • Resource allocation, leasing, or fair-share scheduling and upstream integration, compatibility, or software supply chain integrity.

Benefits & conditions

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 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.

About the company

NVIDIA researchers depend on GPU clusters for large-scale AI workloads. Our DGX Cloud Kubernetes Runtime & Release team brings those clusters to life across major public clouds and specialized GPU providers, often on hardware that is new to the world when we get it. We build and maintain the supported Kubernetes runtime, automate its delivery, and bring new providers and GPU platforms into production.

We’re growing quickly and taking on broader ownership of NVIDIA’s cluster software delivery. We’re hiring across Runtime, Release Engineering, and Provider Integration, with each role focused on your strengths. You don’t need experience across every area below.

What you’ll be doing:

Your primary focus will be one of three areas, with collaboration across the team:

  • Runtime: Build Go controllers and APIs to install, upgrade, and validate GPU cluster software. Integrate components, define API contracts, and evolve Helm and Argo CD delivery toward controller-driven automation.
  • Release Engineering: Build validation pipelines that inform release decisions across providers and GPU platforms. Develop systems to allocate GPU capacity across validation runs and account for cloud reservations and quotas. Make qualification more efficient through reusable tests and clear failure reports.
  • Provider Integration: Bring new providers and GPU hardware into production, potentially among the first engineers working with new silicon. Resolve integration failures with partner teams and turn initial provisioning, upgrade, and operational checks into repeatable automation., This role suits an engineer who wants direct influence over what reaches production, and who builds for the hundredth cluster while shipping the first. Join us and help build the next generation of NVIDIA’s GPU cloud infrastructure!

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