NVIDIA
Senior Software Engineer, Distributed Systems Engineering - DGX Cloud
$184K–$356K
US, CA, Santa Clara +1 · Senior · Full-time · Posted Oct 2, 2026
- Location
- US, CA, Santa Clara
US, Remote - Experience
- 8+ years in a similar role.
- Education
- BS in Computer Science, Engineering, Physics, Mathematics, or a comparable degree or equivalent experience.
About the job
Develop and operate production software for scalable GPU clusters, including Kubernetes-based GPU scheduling, monitoring, and health management for AI workloads.
What you'll do
- Build custom software to schedule GPU resources on Kubernetes and support large-scale production clusters.
- Implement GPU asset monitoring and health management using hardware diagnostics, cluster, and network telemetry.
- Coordinate across teams to improve cluster reliability and performance and address system failures through incident management.
What they ask for
- Software engineering experience in a highly technical organization, with demonstrable impact.
- Software development experience with Kubernetes APIs and frameworks, not just cluster operations.
- Experience with large-scale production systems and common software engineering principles, tools, and techniques.
- BS in Computer Science, Engineering, Physics, Mathematics, or a comparable degree or equivalent experience; systems programming in Go or Python and knowledge of data structures and algorithms.
Nice to have
- Experience managing and automating large-scale distributed systems independent of cloud providers; hands-on experience with Kubernetes, Slurm, or Bright Cluster Manager.
- Operational excellence maintaining reliable, performant AI infrastructure.
Pay
184,000 USD - 287,500 USD base salary (Level 4); 224,000 USD - 356,500 USD base salary (Level 5)
Tools
Kubernetes, Go, Python, Slurm, Bright Cluster Manager
AI focus
Build and operate GPU cluster infrastructure and scheduling, monitoring, and health capabilities that support AI workloads.
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