Senior Linux Infrastructure Specialist

3 days ago

Jamnagar, India beBeeSystem Full time

About the RoleAs a seasoned Senior Linux Administrator, you will be responsible for implementing and managing on-premises Linux servers optimized for AI/ML workloads. This role requires hands-on expertise in Linux system administration, Kubernetes cluster management, and a deep understanding of data center infrastructure components.You will deploy, configure, and manage Linux servers supporting AI/ML applications. 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 languages like Bash and 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.Maintain comprehensive documentation of configurations, policies, and network diagrams. Plan and implement scalability strategies, maintaining uptime and redundancy.Required Skills and Qualifications7+ 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.Ideal Candidate ProfileThe ideal candidate will have a strong track record of success in similar roles. Excellent problem-solving, communication, and collaboration skills are essential. Familiarity with HPC environments and distributed computing frameworks is a plus.Preferred candidates will also have exposure to NVIDIA GPU management, CUDA environments, and AI/ML compute nodes. Knowledge of DevOps practices, containerization, and hybrid cloud environments is also desirable.

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