We are looking for a hands-on Senior ML DevOps and IT Support professional to join our team in Dubai. This is an onsite role where you will help us build, secure, and maintain the critical systems powering our AI infrastructure.
This role sits at the intersection of MLOps, Cloud Networking, and IT Service Management. You will take ownership of the hardware and software foundations for our machine learning workloads while serving as the primary lead for internal IT operations. Based in our Dubai office, you will ensure that both our production GPU environments and our people have the reliable support and connectivity they need to move fast.
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