Azure Machine Learning Platform Engineer

Professional Experience: 5+ years in IT, with extensive hands-on experience building modern cloud infrastructure, with a recent focus on ML Platform Engineering or MLOps., Azure ML & AI Foundry: Deep expertise in deploying and configuring Azure Machine Learning Workspaces and Azure AI Foundry. You understand the ecosystem of Model Registries, Compute Clusters, and how to secure them (Private Links, VNETs)., Kubernetes for Inference: Strong practical experience maintaining AKS (Azure Kubernetes Service) specifically for Kubernetes Online Endpoints. You know how to debug inference errors, manage auto-scaling for model serving, and handle specialized compute (GPU)., GenAI & Vector Stack: Practical experience implementing the infrastructure for RAG (Retrieval-Augmented Generation) architectures. You have worked with Vector Databases (e.g., Azure AI Search, Qdrant, Pinecone) and know how to integrate them into an Azure environment., Infrastructure as Code (IaC): Advanced proficiency with Terraform for provisioning and managing ML resources. You believe that an ML Workspace should be reproducible via code, not clicked together in the portal., CI/CD & MLOps: Mastery of Azure DevOps. You don't just build code pipelines; you understand MLOps—automating model retraining, versioning, and deployment to inference endpoints., Programming: Proficiency in Python (specifically using the Azure ML SDK v2 and CLI) for scripting, automation, and glue code., Strong communication skills and fluent English., Data Engineering Background: Experience with modern data processing and orchestration tools (e.g., Azure Data Factory, Databricks, Fabric, or Airflow). Understanding how to build the data pipelines that feed the ML models is a massive advantage., Advanced Observability: Experience setting up monitoring for model drift, data quality, and inference latency using Azure Monitor or App Insights., Certifications: Active Azure certifications (e.g., Azure DevOps Engineer Expert, Azure Data Engineer Associate), Consultancy experience: Previous experience gained in mid-size/large international client-facing environments, “Hold my beer – I got this” attitude, Insight Geek that needs constant feeding

sharing the costs of sports activities, private medical care, sharing the costs of professional training & courses, life insurance, remote work opportunities, flexible working time, fruits, integration events