Senior Software Engineer - DGX Cloud
Company: Nvidia
Location: US, WA, Seattle (Remote)
Salary: $152k - $241.5k per year
Type: Full-time
Remote: Yes
Posted: 2026-10-01
About this role
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.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA seeks a driven Software Engineer to advance our Kubernetes and AI Observability.
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).
- 5+ years of relevant work experience.
- Expert-level knowledge in systems programming languages (e.g. Go) 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 Ansibl...