Infrastructure - Linux / HPC Engineer AI & ML Platforms:

CRUTZ LEELA ENTERPRISES
Pune, Maharashtra

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Job details

Full-time
₹9,00,000 - ₹20,00,000 a year
8 days ago

Benefits

Provident Fund

Qualifications

CI/CD
Performance tuning
Elasticsearch
TCP
Cloud infrastructure
System administration
Law
Kubernetes
Ansible
Software deployment
Load balancing
DevOps
Git
Master's degree
Bash (Unix shell)
Firewall
Distributed systems
Continuous integration
Ubuntu
Scripting
DNS
Linux
RHCE
TCP/IP
AI
RHCSA
Jenkins
Communication skills
Python
Juniper

Full job description

Infrastructure - Linux / HPC Engineer AI & ML Platforms:

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 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.

Ways to Stand Out from the Crowd:

 Experience with OpenShift or large-scale Kubernetes platform operations.

 Hands-on experience supporting AI/ML and LLM inference platforms at scale,

including working with vLLM for high-performance LLM serving, optimization, and

large-scale inference.

 Experience with infrastructure-as-code, GitOps, or advanced automation frameworks.

 Proficiency with Python, Bash, Ansible, Jenkins, Git, ArgoCD, or similar DevOps

tooling.

 Experience with GPU performance tuning, distributed AI workloads, or HPC

optimization.

 Familiarity with observability platforms such as Prometheus, Grafana,

ELK/Elasticsearch, or distributed tracing systems.

 Experience supporting enterprise AI infrastructure in hybrid cloud or large-scale data

center environments.

 Familiarity with Juniper networking environments or enterprise network operations.

 RHCSA/RHCE, CKA/CKS, or similar infrastructure/platform certifications.

Pay: ₹900,000.00 - ₹2,000,000.00 per year

Benefits:

Provident Fund

Work Location: In person

Quick apply

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