AI Infra & MLOps Engineer — Kubernetes & NVAI

Müller`s Solutions; Dubai; On-site; AED 279,000 - 446,000; Full time

Job summary

Müller’s Solutions seeks an AI Infrastructure & MLOps Engineer on a 6-month contract to lead hands-on implementation, configuration, and setup of AI infrastructure and MLOps workflows. The role is operations-focused (90%) and acts as a technical advisor and hands-on engineer for a strategic AI environment.

The candidate will operate and maintain AI infrastructure, monitor AI workloads, conduct testing, ensure system availability, and support data pipelines for the customer’s AI adoption, with

Qualifications

• Proficient experience with the NVIDIA Enterprise AI Stack.
• Familiarity with Ubuntu Linux.
• Experience with Kubernetes.
• Knowledge of Kubeflow / MLflow.
• Experience with QFLOW (open-source AI data pipeline tool).
• 4–6 years of practical experience in Python and Jupyter Notebook/JupyterLab.

Responsibilities

• Operate and maintain AI infrastructure and MLOps platforms in a production environment.
• Monitor, manage, and troubleshoot Kubernetes-based AI workloads.
• Perform Acceptance Testing Planning and Execution for AI infrastructure and platforms.
• Ensure stability, performance, and availability of AI systems.
• Support day-to-day operational tasks across compute, storage, and networking layers.
• Install and configure NVIDIA Enterprise AI Stack (NVAI).
• Configure and manage MLOps platforms such as Kubeflow and MLflow.
• Assist in setting up end-to-end AI workflows, including data pipelines.
• Support the initial implementation phase of the AI environment.
• Act as a technical guide and advisor to the customer during the early stages of their AI adoption.

Skills

NVIDIA Enterprise AI Stack

Ubuntu Linux

Kubernetes

Kubeflow

MLflow

QFLOW

Python

Jupyter Notebook/JupyterLab

Job description

Müller’s Solutions seeks an AI Infrastructure & MLOps Engineer on a 6-month contract to lead hands-on implementation, configuration, and setup of AI infrastructure and MLOps workflows. The role is operations-focused (90%) and acts as a technical advisor and hands-on engineer for a strategic AI environment.

The candidate will operate and maintain AI infrastructure, monitor AI workloads, conduct testing, ensure system availability, and support data pipelines for the customer’s AI adoption, with