✦ Luna Orbit — AI & Machine Learning

Senior Software Engineer, Cloud-Native Stack - CSP Engagements

at Nvidia

📍 4 Locations Unknown Posted March 13, 2026
Type Not Specified
Experience senior
Exp. Years 6+ years
Education BS or MS in Computer Engineering, Computer Science, or related field
Category AI & Machine Learning

This role involves debugging and optimizing large-scale multi-tenant AI datacenter clusters, focusing on Kubernetes, Slurm, and GPU integration.

  • Debug multi-tenant clusters
  • Prototype stack enhancements
  • Collaborate on architecture reviews
  • Create testbeds and automation
  • Present at conferences and customer sites

Technical environment includes Kubernetes internals, Slurm workload manager, container runtimes, RDMA/IB fabric, and GPU accelerators, with a focus on debugging and system optimization.

The ideal candidate is a senior software engineer with over 6 years of experience in Kubernetes internals, Slurm, and cloud-native stack debugging, with a focus on GPU integration and large-scale systems.

Kubernetes internalsSlurmcontainerized clustersdebugging large-scale cloud-native stacks6+ years of experience
GPU computingCUDAdeep learning workloadsupstream contributions
HelmAnsibleTerraformGitHub ActionsTektonPrometheusOpenTelemetry
KubernetesSlurmcontainer runtimeRDMAIB fabricHelmAnsibleTerraformGoRustC++PythonCI/CDPrometheusOpenTelemetryGPU computingCUDAdeep learning workloads
KubernetesK8sSlurmcontainer runtimeRDMAIB fabricHelmAnsibleTerraformGoRustC++PythonCI/CDPrometheusOpenTelemetry
communicationrequirements gatheringproblem-solvingcollaborationtechnical documentation
Industry Technology
Job Function Debugging, optimizing, and extending cloud-native AI datacenter infrastructure
KubernetesK8sSlurmcontainer runtimeRDMAIB fabricHelmAnsibleTerraformGoRustC++PythonCI/CDPrometheusOpenTelemetryGPU computingCUDAdeep learning workloadsupstream contributions

Less than 6 years of experience, Lack of expertise in Kubernetes internals or Slurm, No experience with GPU computing

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