EMERGYS
Website:
emergys.com
Job details:
Key Responsibilities:
• Deploy, manage, and optimize AI/ML and LLM inference workloads across GPU clusters, HPC infrastructure, and cloud environments.
• Build and maintain scalable AI platform infrastructure using Kubernetes, containers, and enterprise orchestration platforms.
• Administer and optimize Linux servers including system configuration, patching, security hardening, performance tuning, and troubleshooting.
• Manage physical infrastructure including servers, storage, networking, and bare metal environments within enterprise data centers.
• Implement and maintain CI/CD and automation workflows for platform and infrastructure deployments.
• Optimize infrastructure performance, GPU utilization, resource allocation, and distributed workloads to meet operational requirements. • Benchmark and evaluate AI workloads for scalability, latency, throughput, and resource efficiency.
• Collaborate with infrastructure, SRE, and platform engineering teams to provision compute resources and maintain enterprise-scale AI environments.
• Implement monitoring, logging, observability, and alerting solutions for platform reliability and operational visibility.
• Apply security patches, upgrades, compliance controls, and operational best practices for Linux and Kubernetes environments.
• Troubleshoot issues across hardware, networking, operating systems, Kubernetes clusters, and AI/ML workloads.
• Support enterprise operations through efficient incident, change, and ticket management processes.
• Automate infrastructure operations using scripting and infrastructure automation tools.
Required Qualifications:
• 8+ years of experience in Linux systems administration, cloud-native infrastructure, HPC environments, or platform engineering.
• At least 4 years of experience supporting AI/ML workloads or large-scale distributed compute environments in production.
• Comfortable leveraging AI-assisted tools for collaborative development, code generation, refactoring, and productivity enhancement.
• Strong hands-on expertise with Linux administration (RHEL, Ubuntu, or similar).
• Experience with Kubernetes administration, container orchestration, and cloud native infrastructure platforms.
• Strong understanding of GPU infrastructure, distributed computing, and HPC systems.
• Hands-on experience with bare-metal infrastructure, servers, storage systems, and enterprise networking.
• Strong understanding of networking fundamentals including TCP/IP, DNS, load balancing, and firewalls.
• Experience with scripting and infrastructure automation with Bash, Python etc.
• Experience with CI/CD, DevOps, or infrastructure deployment workflows.
• Experience with monitoring, observability, and logging platforms.
• Strong troubleshooting and performance optimization skills across Linux, Kubernetes, networking, and infrastructure stacks.
• Excellent problem-solving, communication, and collaboration skills.
• Ability to work effectively in fast-paced, mission-critical production environments.
Click on Apply to know more.