NVIDIA

4 weeks ago

Systems Software Engineer, Kubernetes Scale - DGX Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Join NVIDIA DGX Cloud to drive end-to-end performance and scale for a distributed AI infrastructure. You will work across Kubernetes, GPU operator components, and cloud platforms to optimize AI workloads at ultra-large scale, build monitoring and CI/CD testing frameworks, and collaborate with researchers, developers, and open-source communities to push the boundaries of scalable AI.

Location: Germany

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack from Kubernetes control and data planes through NVIDIA components.
•Collaborate with researchers, developers and customers to create automated tests simulating real workloads using open-source tools.
•Deep dive into performance and scale issues in complex distributed systems to identify root causes.
•Design and develop monitoring, reporting and analysis tools for performance and scale testing across software, GPU and CPU resources.
•Triage, debug and resolve issues in operating Kubernetes clusters at ultra-large scale and maintain reliable, efficient systems.

Key Requirements

•2+ years of experience in Computer Architecture, Networking, Storage systems, Accelerators, and a engineering degree (Bachelor's or Master's) in Electrical/Computer/CS or equivalent
•Expertise in Kubernetes and familiarity with related CNCF projects
•Background in large-scale parallel and distributed accelerator-based systems
•Expertise optimizing performance and AI workloads on large-scale systems
•Experience with performance modeling and benchmarking at scale

Experience:2+ yearsDistributed systemsKubernetesAI workloadsCloud platforms

Education:Bachelor's

Skills:GolangPythonKubernetes_container toolingDocker

Languages:English

Tech Stack:KubernetesGolangPythonDockerDCGMGPU OperatorNIMNVIDIA software ecosystemCloud platformsCNCF

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

4 weeks ago

Systems Software Engineer, Kubernetes Scale - DGX Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Germany

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack from Kubernetes control and data planes through NVIDIA components.
•Collaborate with researchers, developers and customers to create automated tests simulating real workloads using open-source tools.
•Deep dive into performance and scale issues in complex distributed systems to identify root causes.
•Design and develop monitoring, reporting and analysis tools for performance and scale testing across software, GPU and CPU resources.
•Triage, debug and resolve issues in operating Kubernetes clusters at ultra-large scale and maintain reliable, efficient systems.

Key Requirements

•2+ years of experience in Computer Architecture, Networking, Storage systems, Accelerators, and a engineering degree (Bachelor's or Master's) in Electrical/Computer/CS or equivalent
•Expertise in Kubernetes and familiarity with related CNCF projects
•Background in large-scale parallel and distributed accelerator-based systems
•Expertise optimizing performance and AI workloads on large-scale systems
•Experience with performance modeling and benchmarking at scale

Experience:2+ yearsDistributed systemsKubernetesAI workloadsCloud platforms

Education:Bachelor's

Skills:GolangPythonKubernetes_container toolingDocker

Languages:English

Tech Stack:KubernetesGolangPythonDockerDCGMGPU OperatorNIMNVIDIA software ecosystemCloud platformsCNCF

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor