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Tier-1 brand, mid-level experience, and metro location increase qualified applicant density.
Strong specialization in GPU-accelerated stacks, Kubernetes, and datacenter/CSP environments limits cross-industry transferability.
Explicit 5+ years and mandatory Kubernetes, Python, Linux, and GPU production experience enforce strict shortlisting.
Support and resolve complex customer software issues end-to-end for NVIDIA AI Enterprise deployments across cloud and datacenter environments.
Develop and maintain software features, automation, diagnostics, and deployment tools to improve product readiness and scale support.
Own technically deep escalations from inception to closure, collaborating with customers and engineering teams on fixes and improvements.
Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience).
At least 5+ years of system software development and troubleshooting experience; customer-facing experience preferred.
Strong programming/scripting skills in Python; Bash required, Go/C++ are pluses.
Deep knowledge of Linux; familiarity with GPU-accelerated AI/ML stacks, container platforms (Docker/Kubernetes), and cloud environments (AWS/Azure/GCP).
Experienced in deploying and operating NVIDIA AI Enterprise components in production on-premises or cloud service provider environments.
Strong troubleshooting and debugging skills across application, platform, and infrastructure layers, including performance tuning for GPU and cloud workloads.
Comfortable working in complex Kubernetes-based production environments with knowledge of container orchestration and distributed systems.