Senior Software Engineer, Distributed Systems Engineer - DGX Cloud
Overview:
In this role you will help scale production AI GPU clusters by developing Kubernetes-based scheduling and resource-management software. You will work on DGX Cloud production systems, ensuring reliability and performance across multi-team initiatives. You will analyze failures through incident management and leverage telemetry from GPUs, clusters, and networks. This is a hands-on position that values creativity and execution, offering impact on cutting-edge AI infrastructure. You will collaborate with cross-functional teams to advance NVIDIA's AI deployment capabilities. Compensation / Benefitsequitybenefitsbase salary with levels 3 and 4remote work optionslocation: Santa Clara or US Remotecareer growth opportunities
Responsibilities:
- Develop and extend Kubernetes-based scheduling for GPU resources
- Build and improve cluster health monitoring and incident response processes
- Work on production systems for large scalable GPU clusters
- Integrate hardware diagnostics and telemetry into reliability tooling
- Collaborate with cross-functional teams to maintain high performance and reliability
- Evaluate failures and implement improvements via a defined incident management approach
Key requirements:
- 5+ years in a software engineering role on large-scale production systems
- Software development with Kubernetes APIs and frameworks (not only operations)BS in Computer Science, Engineering, Physics, Mathematics or equivalent
- Proficiency in Go or Python and strong data structures/algorithms
- Strong communication and cross-functional collaboration skillsstrong communicationcross-functional collaborationexecution bias
- Kubernetes APIs and cluster management
- Go or Python programmingGPU resource scheduling