Senior Systems Software Engineer, Containers and Kubernetes

NVIDIA•Austin, TX

9d•$184,000 - $356,500

About The Position

NVIDIA is seeking a Senior Systems Software Engineer to develop platform software based on open-source container runtimes and Kubernetes technologies. The role focuses on making GPU-accelerated applications easier to develop, deploy, and monitor, including enabling GPUs as first-class resources in container orchestrators such as Kubernetes. The engineer will join a small, dynamic team working on cloud-native technologies that enable NVIDIA accelerators in Kubernetes and collaborate with engineering teams across NVIDIA to ensure software integrates throughout the stack. The position calls for strong systems programming and software design skills, distributed systems experience, and the ability to adapt to evolving priorities. NVIDIA describes its work as advancing artificial intelligence, high-performance computing, and visualization.

Requirements

Bachelor’s or master’s degree in Computer Science or a related field, or equivalent experience.
At least 8 years of relevant work experience.
Expert-level knowledge of a systems programming language such as Go or C.
Solid understanding of data structures and algorithms.
Strong understanding of Kubernetes and container technology.
Knowledge and experience with Linux operating system internals.
Strong background in cloud computing and distributed software design and development.
Understanding of performance, security, and reliability in complex distributed systems.
Strong communication and planning skills.

Nice To Haves

Strong experience with Go, containers, and Kubernetes.
Recent active participation and consistent technical contributions to CNCF and Kubernetes SIG projects.
Experience with the Kubernetes Operator framework, Container Device Interface (CDI), and Dynamic Resource Allocation (DRA).

Responsibilities

Explore ways to make GPU-accelerated applications easier to develop, deploy, and monitor.
Enable GPUs as first-class resources in container orchestrators such as Kubernetes.
Contribute to cloud-native technologies that enable NVIDIA accelerators in Kubernetes.
Work with engineering teams across NVIDIA to ensure software integrates seamlessly throughout the stack.
Multitask across different tracks and address evolving priorities.