Azure Machine Learning Platform Engineer (AI Engineering)

TL;DR

Azure Machine Learning Platform Engineer (AI Engineering): Designing and implementing modern, secure Azure AI platforms, enabling Data Science teams to deploy Azure ML Workspaces and GenAI services to production efficiently. Focus on building the underlying architecture for model training, deploying Large Language Models (LLMs), and managing real-time inference at scale.

Location: Remote (any location in Poland)

Company

hirify.global is a European leader in cloud implementation, application development, managed services and training.

What you will do

• Design, architect, and implement modern, secure Azure AI platforms.
• Enable Data Science teams by building a "paved road" for deploying Azure ML Workspaces and utilizing Azure AI Foundry.
• Deploy and configure Azure Machine Learning Workspaces and Azure AI Foundry.
• Maintain AKS (Azure Kubernetes Service) specifically for Kubernetes Online Endpoints, debug inference errors, and manage auto-scaling for model serving.
• Implement the infrastructure for RAG (Retrieval-Augmented Generation) architectures and integrate Vector Databases into Azure environments.
• Automate model retraining, versioning, and deployment to inference endpoints using Azure DevOps.

Requirements

• 8+ years in IT with hands-on experience building modern cloud infrastructure, with a recent focus on ML Platform Engineering or MLOps.
• Deep expertise in deploying and configuring Azure Machine Learning Workspaces and Azure AI Foundry, including securing them with Private Links and VNETs.
• Strong practical experience maintaining AKS (Azure Kubernetes Service) specifically for Kubernetes Online Endpoints, including debugging inference errors and managing auto-scaling for model serving.
• Practical experience implementing the infrastructure for RAG (Retrieval-Augmented Generation) architectures and working with Vector Databases.
• Advanced proficiency with Terraform for provisioning and managing ML resources.
• Mastery of Azure DevOps and understanding of MLOps.
• Proficiency in Python (specifically using the Azure ML SDK v2 and CLI) for scripting, automation, and glue code.
• Strong communication skills and fluent English.
• All applicants must have the right to work in Poland.

Nice to have

• Experience with modern data processing and orchestration tools (e.g., Azure Data Factory, Databricks, Fabric, or Airflow).
• Experience setting up monitoring for model drift, data quality, and inference latency using Azure Monitor or App Insights.
• Active Azure certifications (e.g., Azure DevOps Engineer Expert, Azure Data Engineer Associate).
• Previous consultancy experience gained in mid-size/large international client-facing environments.

Culture & Benefits

• Highly skilled co-workers in a friendly and supportive working culture with knowledge sharing.
• Access to the most advanced technologies and the newest launches.
• Benefits include health care, cafeteria system, life insurance, and access to learning platforms.
• An individual training budget, coverage of certain hyperscaler certification exam fees, and bonuses upon successful certification.
• Great self-development possibilities with internal presentations and workshops.
• Ability to choose your working model from day one – fully remote, fully on-site, hybrid.