Senior MLOps Engineer

About the role

We are looking for a senior MLOps Engineer to design, provision, and maintain GPU‑enabled infrastructure for AI and large language model workloads. The role involves ensuring high availability, scalability, and security of both on‑premises and cloud environments.

Key responsibilities

• Design, deploy and manage GPU‑accelerated compute clusters on‑premises or in Azure, AWS, or GCP.
• Configure and harden Linux operating systems for optimal performance and security.
• Implement container orchestration using Docker and Kubernetes to achieve fault tolerance and scalability.
• Develop and maintain CI/CD pipelines with Azure DevOps, Jenkins, GitHub Actions or GitLab CI.
• Automate infrastructure provisioning with Terraform, ARM templates or CloudFormation.

Required profile

• Bachelor’s or master’s degree in Computer Science, Engineering or a related field.
• 10+ years of DevOps experience with a strong focus on MLOps.
• Hands‑on experience managing GPU infrastructure and Linux system administration.

Required skills

• Linux system administration
• Docker and Kubernetes
• CI/CD tools: Azure DevOps, Jenkins, GitHub Actions, GitLab CI
• Cloud platforms: Azure, AWS, GCP
• Infrastructure as Code: Terraform, ARM, CloudFormation
• Scripting: Python, Bash
• Monitoring: Prometheus, Grafana, ELK stack
• GPU infrastructure setup and management