Senior ML DevOps & IT Support

What You ll Work on

• Manage and scale multi-cluster GPU environments and high-compute AI workloads
• Provide hands-on IT support (user access, device management, and internal systems)
• Design and maintain secure cloud network architectures across Azure and GCP
• Support MLOps pipelines and the deployment of machine learning models
• Administer internal IT infrastructure, including IAM, SSO, and MDM
• Set up monitoring and alerting for GPU health, system performance, and security
• Apply cloud security best practices across infrastructure and endpoint layers
• Troubleshoot and resolve system, deployment, and connectivity issues
• Collaborate with AI engineers to optimize infrastructure for machine learning tasks

Requirements

• 4+ years of experience in IT Administration, Systems Engineering, and DevOps
• Strong experience managing GPU workloads and high-compute server environments
• Expert-level comfort leading IT support as a core daily responsibility
• Practical experience with Azure and Google Cloud Platform (GCP)
• Solid understanding of MLOps workflows or deploying AI models in production
• Knowledge of networking protocols (TCP/IP, DNS, VPNs) and cloud security
• Proficiency in Infrastructure as Code (Terraform) or system automation scripting
• Hands-on experience with Kubernetes and containerized environments
• Strong problem-solving mindset with the ability to support a technical team independently