Description
NVIDIA is seeking a Software Engineer to join their team to build and operate the governed infrastructure platform behind their Electronic Design Automation (EDA) and hardware engineering organization. The successful candidate will have strong programming skills and a deep understanding of distributed systems.
Responsibilities:
- Own the lifecycle of Kubernetes clusters, including control plane, node lifecycle, and fleet-wide upgrades
- Build self-service capabilities for engineering teams to declare what they need and get it automatically
- Extend Kubernetes with controllers and operators, using open-source projects where possible
- Own CI/CD pipelines and shared platform services, such as policy, autoscaling, and observability
- Onboard new teams and sites onto the platform as a repeatable motion
- Work directly with EDA, infrastructure, networking, storage, and hardware engineering teams to deliver scalable solutions
- Share on-call duties, including incident response, root-cause analysis, and capacity planning
Requirements:
- 5+ years of software engineering or infrastructure engineering experience supporting large-scale production systems
- BS in Computer Science, Engineering, Physics, Mathematics, or a related field
- Strong programming experience in Go or Python
- Real production experience operating Kubernetes or a comparable large-scale platform
- Experience building automation that makes decisions and takes action on distributed infrastructure
- Understanding of performance, security, reliability, fault tolerance, state management, and data consistency in complex systems
- Strong communication skills and ability to work optimally across teams, organizations, and geographic regions
Nice to Have:
- Contributions to open-source infrastructure projects
- Experience running Kubernetes on bare metal with tools like Cluster API, Metal3, Ceph, or Cilium
- Hands-on experience with writing operators or the cloud-native ecosystem
- Track record of being the engineer other teams' onboarding or migration efforts route through
- Improved infrastructure reliability, utilization, and recovery time through production-quality automation
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