Sr Systems Engineer Linux – AI Infrastructure

3 weeks ago

India DC Tech Consulting Full time
We are seeking a highly skilled Senior Linux Administrator to join our team, focusing on the implementation and management of on-premises Linux servers optimized for AI/ML workloads. The ideal candidate will have deep expertise in core Linux system administration, with a strong foundation in configuring and optimizing servers for high-performance computing tasks. Responsibilities include deploying and maintaining robust Linux environments, automating system processes, and ensuring security and stability for AI/ML pipelines. While training on NVIDIA technologies will be provided, the candidate must demonstrate proficiency in Linux ecosystem tools, scripting, and troubleshooting complex on-premises systems. This role demands a proactive problem-solver capable of delivering reliable, high-performance infrastructure to support cutting-edge AI/ML initiatives.

Key Responsibilities

- Support deployment and maintenance of NVIDIA GPU-accelerated systems.

- Deploy and support Kubernetes clusters across various environments and distros (e.g., RKE, OpenShift, AKS, EKS, GKE).

- Perform day-to-day system administration across compute, storage, and networking layers.
- Automate infrastructure tasks using Shell scripts, Ansible, or similar tools.

- Collaborate with DevOps, data science, and engineering teams to ensure scalable, resilient infrastructure for AI/ML workloads.

- Monitor infrastructure health and performance; participate in troubleshooting and root cause analysis.

- Extensive experience in managing, configuring, and troubleshooting Linux-based systems (e.g., RHEL, Ubuntu, CentOS, Debian) in enterprise environments, including kernel tuning, system monitoring, and performance optimization.

- Hands-on experience in deploying and configuring Linux servers for AI/ML applications, including setup of GPU-accelerated environments, storage optimization for large datasets (e.g., using RAID, LVM), and ensuring system stability under intensive computational loads—note that training on NVIDIA technologies will be provided.

- Expertise in tuning Linux systems for performance, including CPU/GPU resource allocation, memory management, and I/O optimization, tailored to on-premises setups handling AI/ML training and inference workloads.

- Proven ability to diagnose and resolve intricate problems in Linux environments, such as hardware failures, network bottlenecks, or software conflicts, with a emphasis on minimizing downtime in mission-critical on-premises AI/ML systems.

Qualifications

• Min 7 years of experience in systems engineering or enterprise infrastructure roles.

• Understanding of enterprise storage, networking, and system monitoring tools.

• Scripting and automation experience (e.g., Bash, Python, Ansible).

• Strong communication, documentation, and troubleshooting skills.

• Comfortable working independently in a remote environment.

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