Nvidia Senior Software Engineer - DGX Cloud 

United States, Texas 

922074222

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.

What you will be doing:

• Be part of a small, dynamic team exploring innovative ways to simplify the development, deployment, and monitoring of GPU and DPU accelerated applications.

• Enable GPUs and DPUs as first-class resources in container orchestrators such as Kubernetes.

• Join the core group working on Cloud Native technologies, improving NVIDIA accelerators in the Kubernetes environment.

• Collaborate with engineering teams across NVIDIA to ensure seamless integration of your software.

• Automate and optimize build, test, integration, and release processes for cloud-native applications.

• Efficiently multitask across different projects, addressing evolving priorities effectively.

What we need to see:

• BS/MS in Computer Science or related field (or equivalent experience).

• 8+ years of relevant work experience.

• Expert-level knowledge in systems programming languages (Go, C) with a solid grasp of Data Structures and Algorithms.

• Strong understanding of Container Orchestration Systems (Kubernetes) and Container Technology.

• In-depth knowledge and experience with Unix/Unix-like kernel internals, particularly Linux.

• Hands-on automation experience with frameworks like Ansible and Terraform.

• Proven experience in setting up, maintaining, and automating continuous integration systems.

• 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:

• Extensive experience with the Go programming language.

• Strong background with Gitlab, Argo, Flux, and other CI/CD systems.

• Significant hands-on experience with Containers and Kubernetes.

• Hands-on experience with container workload isolation and confidential computing.