Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud
About the role
The DGX Cloud organization at NVIDIA brings together cutting-edge hardware and software innovation to deliver industry-leading accelerated computing for the world's most adventurous AI workloads. We are seeking a Senior Systems Software Engineer with deep expertise in distributed systems, open-source technologies like Kubernetes and containers, and a strong background in systems performance and scalability.
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 such as GPU Operator, Network Operator, DCGM, NIM, and distributed inference serving, following issues from orchestration down to the metal.
- Collaborate with AI researchers, developers and customers to develop innovative, automated tests that simulate real user workloads using custom-built and leading open-source tools and frameworks.
- Deep dive into performance and scale issues in complex distributed systems, including interactions between Kubernetes and the NVIDIA software stack, 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.
- Build and maintain a high-velocity framework that enables continuous, always-on performance and scale testing via a modern CI/CD pipeline.
- Document research, methodologies and results clearly and concisely, and present findings at internal and external venues, including community conferences such as KubeCon and GTC.
- Engage efficiently with upstream communities — including Kubernetes, CNCF and NVIDIA open-source projects — to validate performance and scalability of AI workloads early and help shape design and development decisions.
Requirements
- 8+ years of experience in Computer Architecture, Networking, Storage systems, Accelerators and Bachelors/Masters in Engineering (preferably, Electrical Engineering, Computer Engineering, or Computer Science) or equivalent experience.
- Expertise in Kubernetes and familiarity with related CNCF projects.
- Background in working with large scale parallel and distributed accelerator-based systems.
- Experience optimizing performance and AI workloads on large scale systems.
- Proficiency in Golang/Python.
- Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI for example).
Qualifications
- Strong operational experience with any one of the Kubernetes distributions.
- Prior experience scaling Kubernetes clusters to ultra-large node and object counts.
- Demonstrated history of working in the open-source community.
- Excellent communication and interpersonal abilities.
Skills
- Performance modeling and benchmarking at scale.
- Experience with public CSP infrastructure.
Benefits
Base salary range: $184,000 - $287,500 for Level 4, and $224,000 - $356,500 for Level 5. Eligible for equity and benefits.
Pay
Commensurate with experience.
Schedule
N/A
Benefits
N/A
Skills
- Performance modeling and benchmarking at scale.
- Experience with public CSP infrastructure.
Benefits
N/A
Application Instructions
Applications for this job will be accepted at least until June 28, 2026.
Company Information
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.