Dell AI Infrastructure & MLOps Engineer - (6 Month Only)

As an AI Infrastructure & MLOps Engineer at Müller’s Solutions for a 6-month contract, this role is primarily operations-focused (90%), with hands‑on involvement in implementation, configuration, and setup of AI infrastructure and MLOps workflows.You will play a key role in managing, operating, and guiding the deployment of a strategic AI environment, working closely with the customer as a technical advisor and hands‑on engineer.What about the role 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.What should you have to fit in this role?Technical RequirementsAI / MLOps StackProficient experience with the NVIDIA Enterprise AI StackFamiliarity with Ubuntu LinuxExperience with KubernetesKnowledge of Kubeflow / MLflowExperience with QFLOW (an open‑source AI data pipeline management tool)Programming & Automation4–6 years of practical experience in:PythonJupyter Notebook / JupyterLabCompetence in writing, testing, and maintaining operational scripts and AI workflows.Infrastructure ExperiencePractical experience with enterprise infrastructure, encompassing:Dell PowerScale (5 nodes)XE Server (1 node)Dell R570 Servers (5 nodes)Dell Network Switches (2 switches)GPU‑based AI servers (in a small‑scale environment)Environment OverviewInitial implementation of AICompact configuration:1 GPU server1 PowerScale5 control plane serversOpportunity to shape best practices from the ground upTo succeed in this role, it's nice to have:• Familiarity with data frameworks like Apache Spark or Hadoop for data processing.• Understanding of ML model monitoring and logging practices to ensure system reliability.• Experience with security best practices in AI systems.#J-18808-Ljbffr