DevOps Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

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

• Build and maintain infrastructure across bare-metal, virtualized, and containerized environments using advanced technologies and high-end hardware. • Drive continuous improvements across CI/CD pipelines and automation workflows. • Provide infrastructure and automation support for development and verification teams, enabling efficient development and testing processes. • Support development and integration activities for next-generation infrastructure and software platforms. • Improve reliability, scalability, and operational efficiency across Linux- and Windows-based environments.

🎯 Requirements

• 2+ years of experience developing CI/CD processes and contributing in DevOps environments, with a strong passion for automation. • Hands-on experience with CI/CD tools such as Jenkins and GitLab CI. • Extensive experience with hardware-focused infrastructure, including bare-metal and virtualization platforms. • 2+ years of experience working with Linux distributions such as CentOS, Ubuntu, SLES, or Red Hat. • Strong scripting skills in Bash, Python, Groovy. • Good knowledge of virtualization in Linux, including QEMU/KVM, and container orchestration with Kubernetes. • Experience with source control platforms such as GitHub and GitLab. • Understanding of Linux packaging software, including .rpm and .deb. • BSc in Computer Science, Engineering, Information Technology, or similar. • Experience with agentic AI tools, AI-driven automation, or integrating AI into DevOps workflows. • Strong networking knowledge, including TCP/IP, switching, routing, and troubleshooting in Linux- and Windows-based environments. • Experience with PyTest or similar testing frameworks. • Good understanding of the C/C++ toolchain in Linux, including cross-compilation and build tools such as make, cmake, and meson.