Note: The job is a remote job and is open to candidates in USA. GMI Cloud is an AI-native infrastructure company delivering GPU compute, inference services, and infrastructure for AI agents. The Site Reliability Engineer will ensure the stability, efficiency, and reliability of large-scale AI/ML clusters by maintaining infrastructure, automating operations, managing GPU node lifecycles, and responding to infrastructure incidents and customer provisioning requests.
Responsibilities
- Design, implement and maintain scalable AI/ML infrastructure solutions
- Proactively monitor GPU cluster health, performance and troubleshoot issues across compute, accelerator, and storage systems
- Automate deployment, configuration and management of infrastructure resources
- Manage GPU node lifecycle workflows, including provisioning, scaling, maintenance, decommissioning and upgrades of GPU nodes
- Implement CI/CD pipelines for infrastructure deployment and orchestration
- Ensure security, compliance and best practices across infrastructure
- Manage incident response related to Infrastructure resources (GPU, CPU, Storage, Network)
- Handle customer provisioning requests for GPU resources, including onboarding, configuration and troubleshooting; resolve customer service requests related to GPU infrastructure, ensuring high customer satisfaction
- Stay current with emerging GPU hardware and software technologies, integrating improvements as appropriate
- Regional/international travel to GMI data center locations
Skills
- 1. Bachelor's degree in Computer Science or related field
- 2. Over 3+ years of experience in data center operations, infrastructure, or systems engineering
- 3. Proven experience in site reliability engineering and infrastructure automation (e.g. Ansible, Terraform)
- 4. Familiarity with containers orchestration platform (e.g. Kubernetes, Nvidia GPU operator, Nvidia Network operator, CNI, CSI) and job scheduling systems (e.g. Slurm)
- 5. Familiarity with Linux system administration and scripting (Python, Bash)
- 6. Familiarity with logging and monitoring tools such as Prometheus, Grafana, Loki
- 7. Good knowledge of GPU architecture, Nvidia CUDA, NCCL, or related AI/ML frameworks - added advantage
- 8. Strong troubleshooting skills and ability to analyze system logs and performance metrics
- 9. Excellent communication and teamwork abilities
Company Overview
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