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# Senior Systems Software Engineer, Containers, Kubernetes, and Confidential Computing

- **Company:** NVIDIA Ltd.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Unix, Cloud Computing, Computer Programming, Data Structures, Linux, Distributed Systems, Open Source Technology, Software Construction, Software Engineering, System Programming, Virtualization Technology, Graphics Processing Unit (GPU), Containerization, Kubernetes, Information Technology
- **Published:** October 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c55cfd2572949966

## About the Role

* BS/MS in Computer Science, or related field (or equivalent experience)
 * 8+ years of relevant work experience.
 * Expert-level knowledge in a systems programming language (Go, Rust) and solid understanding of Data Structures and Algorithms.
 * Strong understanding of Container Orchestration Systems (K8s) and Container Technology.
 * Expert knowledge and experience working with System internals of Unix/Unix-like kernels such as Linux.
 * Strong background in Cloud Computing and Distributed Software design and development.
 * Understanding of performance, security, and reliability in complex distributed systems.

Ways to stand out from the crowd:

 * Strong experience with Rust and Go programming languages.
 * Real-world strong hands-on experience with Containers and Kubernetes.
 * Proficient with Kata Containers and Container sandboxing technologies
 * Well-versed in Attestation concepts, Key Broker Service, etc.
 * Knowledgeable with virtualization technologies, SR-IOV, vGPU, etc.

## Description

* You'll be part of a small and dynamic team that explores innovative ways to make GPU-accelerated applications easier to develop, deploy, and monitor.
 * Work on enabling GPUs as first-class resources in container orchestrators such as Kubernetes.
 * This is an excellent opportunity to join the core group working on Cloud Native technologies enabling NVIDIA accelerators in the k8s environment.
 * Work with engineering teams across all of NVIDIA to ensure your software integrates seamlessly up and down the stack.
 * Proficiently multitasking on different tracks to efficiently address evolving priorities.