Senior Systems Engineer
3 weeks ago
Summary:
An experienced Systems Engineer with over 10 years of specialized expertise in Linux platforms, Kubernetes cluster management, and advanced troubleshooting. Skilled in Kubernetes Day 2 operations, Linux networking, Linux storage, and Nvidia GPU configurations within Kubernetes environments. Proficient in supporting AI/ML workflows, optimizing infrastructure for performance and reliability, and collaborating with data science teams to facilitate AI/ML tools on Linux and Kubernetes infrastructure.
Key Responsibilities:
Kubernetes Cluster Management:
• Design, deploy, and manage Kubernetes clusters, ensuring optimal performance, scalability, and security.
• Oversee Kubernetes Day2 operations, including lifecycle management, patching, upgrading, and continuous monitoring.
• Develop and implement best practices for Kubernetes cluster security, multi-tenancy, and resource optimization.
Kubernetes Troubleshooting & Maintenance:
• ProactivelytroubleshootandresolvecomplexissuesrelatedtoKubernetesclusters, containers, and networking.
• Perform in-depth diagnostics of cluster performance, node scaling, and API responsiveness.
• Support teams in resolving persistent Kubernetes issues and providing documentation for recurring issues.
Linux Systems Administration:
• Manage Linux-based servers and configurations, ensuring systemst ability and security across all environments.
• Oversee network configuration, DNS management, and performancetuningforLinux systems.
• CoordinatewithstorageteamstomanageLinux-basedstorage,optimizefilesystems,and ensure high availability.
Nvidia GPU Configurations & AI/ML Support:
• Configure and manage Nvidia GPUs in Kubernetes clusters to support GPU-intensive workloads.
• Collaborate with datascience teams tosupport AI/ML workflows,i ncluding model training, inference, and scaling on Kubernetes.
• Understandand troubleshoot AI/ML tools and platforms deployedon Kubernetes, optimizing resources for high-performance computing.
Cross-Functional Collaboration:
• Partner with DevOps, DataEngineering, and DataScience teams to ensure infrastructure supports AI/ML requirements.
• Document and provide knowledge sharing on best practices, configurations, and troubleshooting procedures.
• Participate in on-callrotation to provide high-priority support for production incidents.
Required Skills:
•
Technical Expertise:
• 10+years of experience withLinux systems administration and troubleshooting.
• Strong knowledgeof Kubernetescluster management, including Day2 operations and troubleshooting.
• Deep understanding of Linux networking, storage, and security practices.
• Hands-on experience with Nvidia GPU configurationin Kubernetes environments.
• Familiarity with AI/ML workflows, tools, and best practices in a Linux/Kubernetes environment.
Problem-Solving Abilities:
Demonstrated experience with advanced troubleshooting in both Kubernetes andLinux.
Ability to analyze and resolve complex technical issues efficiently.
Strong focus on performance tuning and optimization.
•
Preferred Qualifications:
Certifications in Kubernetes (CKA/CKAD/CKS) or Linux (RHCE).
Familiarity with monitoring tools like Prometheus, Grafana, or ELK stack.
Experience with AI/ML frameworks such as TensorFlow, PyTorch, or NVIDIA Triton Inference Server.
Soft Skills:
Strong analytical and communication skills.
Ability to work independently and within a collaborative team environment.
Adaptable to changing priorities and a fast-paced work environment.
This role offers the opportunity to work on cutting-edge technology infrastructure, playing a critical part in enabling and supporting the organization’s AI and ML goals.
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