AI/ML Automation Analyst – MLOps & Container Orchestration

About the role

The AI/ML Automation Analyst will join the KSL AI Support Team at KAUST, focusing on building and maintaining MLOps infrastructure, container orchestration, and workflow automation for supercomputing environments. The role ensures researchers can efficiently deploy and manage AI/ML workloads using secure, OCI‑compliant containers and cloud‑native pipelines.

Key responsibilities

• Provide user support via phone, email, walk‑in and ticketing for AI/ML inquiries.
• Develop and maintain secure, OCI‑compliant, HPC‑ready container images for AI/ML and data‑science workloads.
• Design, implement, and operate CI/CD pipelines and MLOps workflows at supercomputing scale.
• Create and expose APIs for AI/ML services and inference endpoints.
• Manage Kubernetes orchestration, including CNI, CSI, and service‑mesh configurations.
• Operate container registries (Harbor) and model registries (MLFlow, Kubeflow).
• Assist with computational readiness and compliance reviews for AI research projects.
• Perform performance debugging, tuning, and benchmarking of MLOps workloads.
• Deploy observability stacks using Prometheus, Grafana, NVIDIA DCGM, and Loki.

Required profile

• At least 1 month of relevant experience in MLOps, containerization, or related fields.
• Strong problem‑solving skills and ability to support diverse research users.
• Familiarity with security and compliance standards for container images and workflows.

Required skills

• Containerization
• Go
• Bash scripting
• MLops
• Linux
• Kubernetes
• Python
• API development