{"id":632617,"url":"https://alion.io/job/mullerssolutions-dell-ai-infrastructure-mlops-engineer-6-month-only","title":"Dell AI Infrastructure & MLOps Engineer - (6 Month Only)","company":{"id":8095,"name":"Müller's Solutions","domain":"mullerssolutions.com","url":"https://alion.io/company/mullerssolutions","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"D","score":46,"open_postings":343,"ghost_share":0.904,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dubai, United Arab Emirates"],"countries":["AE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Jupyter Notebook","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"Ubuntu","optional":false},{"name":"Hadoop","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-01-29T00:00:00Z","employer_posted_date":"2026-01-29","last_verified_at":"2026-10-31T10:44:10Z","board_verified":true,"closed_at":null,"days_open":275,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":275},"description":"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.\nYou 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.\nWhat about the role responsibilities?\nOperate and maintain AI infrastructure and MLOps platforms in a production environment. \n Monitor, manage, and troubleshoot Kubernetes-based AI workloads. \n Perform Acceptance Testing Planning and Execution for AI infrastructure and platforms. \n Ensure stability, performance, and availability of AI systems. \n Support day-to-day operational tasks across compute, storage, and networking layers.\nInstall and configure NVIDIA Enterprise AI Stack (NVAI). \n Configure and manage MLOps platforms such as Kubeflow and MLflow. \n Assist in setting up end-to-end AI workflows, including data pipelines. \n Support the initial implementation phase of the AI environment. \n Act as a technical guide and advisor to the customer during the early stages of their AI adoption.\nRequirements\nWhat should you have to fit in this role?\nTechnical Requirements\nAI / MLOps Stack\nProficient experience with the NVIDIA Enterprise AI Stack\nFamiliarity with Ubuntu Linux\nExperience with Kubernetes\nKnowledge of Kubeflow / MLflow\n Experience with QFLOW (an open-source AI data pipeline management tool)\nProgramming & Automation\n4-6 years of practical experience in:\nPython\nJupyter Notebook / JupyterLab\nCompetence in writing, testing, and maintaining operational scripts and AI workflows.\nInfrastructure Experience\nPractical experience with enterprise infrastructure, encompassing:\n Dell PowerScale (5 nodes)\n XE Server (1 node)\n Dell R570 Servers (5 nodes)\n Dell Network Switches (2 switches)\n GPU-based AI servers (in a small-scale environment)\nEnvironment Overview\nInitial implementation of AI\nCompact configuration:\n1 GPU server\n1 PowerScale\n5 control plane servers\n Opportunity to shape best practices from the ground up\nTo succeed in this role, it's nice to have:\nFamiliarity with data frameworks like Apache Spark or Hadoop for data processing.\nUnderstanding of ML model monitoring and logging practices to ensure system reliability.\nExperience with security best practices in AI systems.","description_format":"text","description_chars":2441,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Managed IT Services (MSP)","Enterprise Apps Implementation Partners","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-09-10T19:25:31Z"}],"visa":[],"liveness":{"score":2,"band":"cold","label":"Long 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