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Tier-1 employer, metro location, and senior systems/cloud title drive moderate applicant competition.
GPU-focused cloud-platform work reduces cross-industry transferability despite transferable Kubernetes and systems skills.
Explicit 8+ years plus mandatory Kubernetes, systems programming, and cloud platform experience increases strictness.
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Improve performance, reliability, and scalability of a distributed system routing AI workloads onto GPU fleets.
Design and develop cloud-native services using Java, Go, and Rust on an open-source platform with both control plane and edge deployments.
Automate build, test, integration, and release processes and collaborate across teams to integrate with NVIDIA technologies.
Bachelor’s or Master’s Degree in Computer Science or equivalent.
8+ years of hands-on software engineering experience.
Expertise in a systems programming language such as Go, C, or Rust, with strong understanding of data structures, algorithms, and distributed software architecture.
Strong knowledge and hands-on experience with Kubernetes, container technologies, scripting (Bash/Python), and Unix-like system internals.
Experienced in distributed systems with focus on performance, security, and reliability.
Skilled in container orchestration and automation using tools like Gitlab and ArgoCD in cloud-native environments.
Familiarity with pub-sub messaging models, high-throughput network optimization (HTTP/2, gRPC), and Kubernetes Custom Resources/Operators.