Senior Software Engineer – Accelerated Kubernetes Runtime Team

🕒 April 7

☕ Washington – Remote

☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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👻 Ghost score 46%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Design and implement runtime features that orchestrate the lifecycle of runtime components across thousands of Kubernetes clusters without manual intervention • Build and maintain systems that configure, package, validate, and distribute accelerated compute components • Develop Kubernetes controllers, CRDs, and operators that automate runtime installation, upgrade, and rollback operations with API-driven workflows • Build next-generation GPU-accelerated Kubernetes runtime distributions for NVIDIA AI Accelerators • Optimize runtime components for GPU architectures including GB200/GB300 and Vera Rubin

🎯 Requirements

• Bachelors in Computer Science, or equivalent experience • 8+ years of professional experience, with at least 3 years of experience with Kubernetes development • Experience building production Kubernetes systems with significant expertise in controllers, operators, and CustomResourceDefinitions • Strong proficiency in Go and experience building scalable Go services that manage complex distributed systems • Hands-on experience with Helm, Kustomize, and managing Kubernetes manifest packaging and templating • Demonstrated ability to design and implement automation systems that replace manual processes with reliable, self-service tooling • Experience working with NVIDIA Kubernetes components such as GPU operator, device plugins, or other HPC components in large scale production environments • Deep familiarity with OCI registries, artifact signing, SBOM generation, and supply chain security practices • Experience building multi-tenant platform services with focus on API design, versioning, and backward compatibility • Track record of migrating legacy systems to modern, automated platforms while maintaining zero-downtime operations and contributions to upstream Kubernetes/CNCF projects or experience extending Kubernetes API machinery • Deep understanding of Kubernetes architecture including API machinery, admission controllers, and resource lifecycle management

🏖️ Benefits

• Equity • Benefits

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