NVIDIA

4 weeks ago

Senior 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

We are seeking an experienced Senior Systems Software Engineer to drive end-to-end performance and scale characterization for NVIDIA DGX Cloud. You will tackle distributed Kubernetes-based AI workloads, optimize stack performance, collaborate with researchers and customers, build monitoring and CI/CD tooling, and engage with upstream communities to shape design and development for ultra-large-scale AI infrastructure.

Location: Germany, United Kingdom, Spain, Poland, Switzerland, France

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, from Kubernetes control/data planes through NVIDIA components such as GPU Operator, Network Operator, DCGM, NIM, and distributed inference serving, tracing issues from orchestration to the metal
•Collaborate with AI researchers, developers and customers to develop innovative automated tests that simulate real workloads using open-source tools and frameworks
•Deep dive into performance and scale issues in complex distributed systems to identify and resolve root causes
•Design and develop monitoring, reporting and analysis tools for performance and scale testing across software, GPU and CPU resources
•Triage, debug and root cause issues related to operating Kubernetes clusters at ultra-large scale, ensuring reliability and efficiency

Key Requirements

•8+ years of experience in Computer Architecture, Networking, Storage systems, accelerators, and a Bachelor's or Master's in Engineering (Electrical, Computer Engineering, or Computer Science) or equivalent experience
•Expertise in Kubernetes and familiarity with 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
•Proficiency in Golang and Python
•Background with the NVIDIA software ecosystem in training and inference
•Experience with at least one public cloud infrastructure (GCP, AWS, Azure, OCI)

Experience:8+ yearsAIKubernetesCloudDistributed systemsGPUDGXNVIDIA software ecosystem

Education:Bachelor's in Engineering

Skills:KubernetesGolangPythonContainersCI/CDMonitoringDistributed systemsOpen-sourceCNCFGPU OperatorDCGMNIMGPUInference serving

Tech Stack:KubernetesGolangPythonContainersCI/CDGPU OperatorDCGMNIMNVIDIA software ecosystemCNCF

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

Loading job details...

Preparing the role view and application actions.

NVIDIA

4 weeks ago

Senior 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, United Kingdom, Spain, Poland, Switzerland, France

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, from Kubernetes control/data planes through NVIDIA components such as GPU Operator, Network Operator, DCGM, NIM, and distributed inference serving, tracing issues from orchestration to the metal
•Collaborate with AI researchers, developers and customers to develop innovative automated tests that simulate real workloads using open-source tools and frameworks
•Deep dive into performance and scale issues in complex distributed systems to identify and resolve root causes
•Design and develop monitoring, reporting and analysis tools for performance and scale testing across software, GPU and CPU resources
•Triage, debug and root cause issues related to operating Kubernetes clusters at ultra-large scale, ensuring reliability and efficiency

Key Requirements

•8+ years of experience in Computer Architecture, Networking, Storage systems, accelerators, and a Bachelor's or Master's in Engineering (Electrical, Computer Engineering, or Computer Science) or equivalent experience
•Expertise in Kubernetes and familiarity with 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
•Proficiency in Golang and Python
•Background with the NVIDIA software ecosystem in training and inference
•Experience with at least one public cloud infrastructure (GCP, AWS, Azure, OCI)

Experience:8+ yearsAIKubernetesCloudDistributed systemsGPUDGXNVIDIA software ecosystem

Education:Bachelor's in Engineering

Skills:KubernetesGolangPythonContainersCI/CDMonitoringDistributed systemsOpen-sourceCNCFGPU OperatorDCGMNIMGPUInference serving

Tech Stack:KubernetesGolangPythonContainersCI/CDGPU OperatorDCGMNIMNVIDIA software ecosystemCNCF

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