Azure Machine Learning Platform Engineer
Posted 52ds ago
Employment Information
Report this job
Job expired or something wrong with this job?
Job Description
Machine Learning Platform Engineer responsible for implementing secure Azure AI platforms at Nordcloud. Collaborating with Data Science teams to deploy Azure ML Workspaces and ship GenAI services.
Responsibilities:
- Responsible for designing, architecting, and implementing modern, secure Azure AI platforms.
- Act as an enabler for Data Science teams, building the "paved road" that allows them to deploy Azure ML Workspaces.
- Utilize Azure AI Foundry and ship GenAI services to production securely and efficiently.
Requirements:
- 8+ years in IT with extensive 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.
- Strong practical experience maintaining AKS (Azure Kubernetes Service) specifically for Kubernetes Online Endpoints.
- Practical experience implementing the infrastructure for RAG (Retrieval-Augmented Generation) architectures.
- Advanced proficiency with Terraform for provisioning and managing ML resources.
- Mastery of Azure DevOps.
- Proficiency in Python (specifically using the Azure ML SDK v2 and CLI).
- 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 experience gained in mid-size/large international client-facing environments.
- Strong communication skills and fluent English.
Benefits:
- Highly skilled co-workers in a friendly and supportive working culture; we enjoy working, having fun together and sharing our knowledge
- The most advanced technologies: we are the overly excited techies who can’t wait to read about the newest launches!
- Benefits like health care, cafeteria system, life insurance, access to learning platforms
- An individual training budget , coverage of certain hyperscaler certification exam fees and bonuses upon successful certification
- Great self-development possibilities – we organise internal presentations and workshops.
- Ability to choose your working model from day one – fully remote, fully on-site, hybrid - your choice!



















