Senior Software Engineer, Kubernetes and Virtualization - DGX Cloud

Responsibilities

• Maintain and develop Kubernetes operators and our Container Storage Interface (CSI) plugin.
• Develop a web-based solution that manages, operates and monitors our distributed storage.
• Work closely with other teams to define and implement new APIs.
• What We Need to See:
• B.Sc., M.Sc. or Ph.D. in Computer Science, or related discipline, or equivalent experience.
• 8+ years of experience in web development (both client and server)
• Proven experience with Kubernetes (K8s), including developing or maintaining operators and/or CSI plugins.
• Experience scripting with Python, Bash or similar. Experience with nodejs is a must
• At least 5 years of experience working in a Linux OS environment
• You're smart and a quick learner
• You do what it takes to get the job done
• Passionate about coding and big challenges
• Ways to stand out from the crowd:
• NodeJS for the server side: dominant modules are async & express. Kafka, MongoDB, K8s
• JavaScript frameworks: React, jQuery, c3j
• HTML5, CSS3, Bootstrap and Websockets; Scripting (Python and Bash) as well as Git and Linux
• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits .
• Applications for this job will be accepted at least until June 26, 2026. This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.

Additional Information

We are looking for a Senior Software Engineer to become part of our storage management plane team. The management plane is a web-based application crafted to provide our storage customers the capabilities to handle and supervise our distributed storage infrastructure. Our team is continually dedicated to acquiring and implementing ground breaking technologies to overcome obstacles and innovate solutions for improving our ability to handle large clusters of machines efficiently.

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