Infrastructure Engineer | Emergys Skip to content Toggle Navigation Services AI & Data Agentic AI Intelligent Automation Data Engineering Big Data & Cloud AIOps BI and Visualization Inference Engineering Enterprise Solutions SAP BMC ServiceNow Salesforce ServiceRize Freshworks Modern Applications Product Development Platform Engineering Low-Code No-Code Testing Check Out Our Innovative Solutions For enterprises, Emergys creates a way to scale and accelerate digital transformation while giving their customers access innovations and solutions. AI & Data Agentic AI Intelligent Automation Data Engineering Big Data & Cloud AIOps BI and Visualization Inference Engineering Enterprise Solutions SAP BMC ServiceNow Salesforce ServiceRize Freshworks Modern Applications Product Development Platform Engineering Low-Code No-Code Testing Accelerators Industries Company Insights Blogs Brochures eBooks Success Stories Webinars Infographics News Videos Whitepapers Careers Contact Infrastructure Engineer Job Position: Infrastructure – Linux / HPC Engineer AI & ML Platforms Location: Pune, India We are seeking a highly skilled Linux / HPC Infrastructure Engineer to support and scale enterprise AI/ML and LLM platforms across GPU clusters, Kubernetes environments, and data center infrastructure. This role combines expertise in Linux systems, Kubernetes administration, HPC infrastructure, GPU-accelerated AI workloads, and enterprise platform operations. You will be responsible for designing, deploying, optimizing, and maintaining highly available AI infrastructure environments supporting large-scale inference, distributed computing, and cloud-native AI platforms. 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 system