Expertise in AI-Powered Linux Systems

1 week ago

bareilly, India beBeeKubernetes Full time

Linux Systems Engineer for AI InfrastructureWe seek an experienced Linux systems engineer to manage on-premises Linux servers optimized for artificial intelligence and machine learning workloads. The ideal candidate will possess in-depth knowledge of Linux system administration, Kubernetes cluster management, and a strong understanding of data center infrastructure components including servers, networking, storage, and virtualization technologies.Key Responsibilities:Deploy, configure, and manage on-premises Linux servers supporting AI/ML workloads.Set up, manage, and troubleshoot Kubernetes clusters for containerized workloads.Optimize system and network performance for compute-intensive applications.Automate provisioning and configuration using Ansible, Terraform, and scripting (Bash/Python).Administer and monitor data center components such as servers, storage arrays, switches, and power systems.Ensure system security, patch management, and compliance across environments.Collaborate with DevOps, Data Science, and AI engineering teams to enable seamless integration with ML pipelines.Plan and implement scalability strategies, maintaining uptime and redundancy.Maintain comprehensive documentation of configurations, policies, and network diagrams.Required Skills & Qualifications:7+ years of experience in Linux system administration (RHEL, Ubuntu, CentOS).Proven hands-on experience with Kubernetes cluster management (setup, scaling, troubleshooting).CKA (Certified Kubernetes Administrator) certification is mandatory.Strong knowledge of data center components – servers, racks, networking switches, storage systems, and virtualization layers.Experience with Ansible, Terraform, CI/CD pipelines, and infrastructure automation.Proficiency in scripting languages (Bash, Python).Understanding of performance tuning, system optimization, and fault diagnosis.Excellent problem-solving, communication, and collaboration skills.Preferred / Good to Have:Exposure to NVIDIA GPU management, CUDA environments, and AI/ML compute nodes.Familiarity with HPC environments and distributed computing frameworks.Experience managing monitoring systems (Prometheus, Grafana) and backup solutions.Knowledge of DevOps practices, containerization, and hybrid cloud environments.

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