NVIDIA

4 weeks ago

Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Lead and optimize Kubernetes-based accelerated runtime stacks for DGX Cloud, driving end-to-end performance, scalability, and reliability across thousands of GPU nodes. You’ll contribute to upstream Kubernetes control plane changes, enhance container startup, and collaborate with open-source communities to advance AI workloads at hyperscale, balancing cost, latency, and resilience in production AI factories.

Location: Santa Clara, Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack, including NVIDIA components, tracking issues from orchestration down to the metal.
•Design and contribute upstream architectural changes to the Kubernetes control plane for operation at hyperscale cluster sizes.
•Improve container startup and cold-start latency to enable low-latency inference scaling on Kubernetes across thousands of GPU nodes.
•Assess, improve, and contribute to open-source projects that enable Kubernetes for AI workloads, focusing on scalability, resilience, and multi-node training/inference.
•Advance scalability and performance of confidential containers (CoCo) on Kubernetes for encrypted inference workloads in production.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•Bachelor’s or Master’s degree in Engineering or equivalent experience
•8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms
•Expertise in Kubernetes and familiarity with the broader CNCF ecosystem
•Deep experience with large-scale, parallel, distributed accelerator systems and performance optimization of AI workloads
•Proficiency in Golang and/or Python

Experience:8+ yearsAICloudDistributed systemsGPUAccelerated computing

Education:Bachelor's

Skills:GolangPythonKubernetesContainersGPUCloud platforms

Languages:English

Tech Stack:GolangPythonKubernetesDockerGPU OperatorNVIDIA software stackAWSAzureGCPOCIGateway-api-inference-extensionGroveKubeConNVIDIA OSS

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

Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Santa Clara, Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack, including NVIDIA components, tracking issues from orchestration down to the metal.
•Design and contribute upstream architectural changes to the Kubernetes control plane for operation at hyperscale cluster sizes.
•Improve container startup and cold-start latency to enable low-latency inference scaling on Kubernetes across thousands of GPU nodes.
•Assess, improve, and contribute to open-source projects that enable Kubernetes for AI workloads, focusing on scalability, resilience, and multi-node training/inference.
•Advance scalability and performance of confidential containers (CoCo) on Kubernetes for encrypted inference workloads in production.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•Bachelor’s or Master’s degree in Engineering or equivalent experience
•8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms
•Expertise in Kubernetes and familiarity with the broader CNCF ecosystem
•Deep experience with large-scale, parallel, distributed accelerator systems and performance optimization of AI workloads
•Proficiency in Golang and/or Python

Experience:8+ yearsAICloudDistributed systemsGPUAccelerated computing

Education:Bachelor's

Skills:GolangPythonKubernetesContainersGPUCloud platforms

Languages:English

Tech Stack:GolangPythonKubernetesDockerGPU OperatorNVIDIA software stackAWSAzureGCPOCIGateway-api-inference-extensionGroveKubeConNVIDIA OSS

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