Azure ML Engineer
Galileo Global Education28 days ago
Budapest, HungarySenior
Responsibilities
- Design and implement end-to-end machine learning pipelines on Azure and Databricks.
- Deploy, monitor, retrain, and version machine learning models in production.
- Build and maintain MLOps processes using CI/CD, infrastructure as code, and automated testing.
- Define Azure resources, Databricks compute, and deployment patterns with emphasis on cloud cost optimization.
- Integrate ML solutions with lakehouse platforms and existing data pipelines.
- Collaborate with data engineers, architects, business stakeholders, and external vendors.
- Review vendor solutions for alignment with internal architecture, security, and operational standards.
- Contribute reusable ML platform components, technical standards, and documentation.
- Technically oversee external vendors through architecture and solution reviews.
Requirements
- Strong practical experience in ML engineering and MLOps, including production model deployment, operation, monitoring, retraining, and versioning.
- Strong Python skills and practical experience with PySpark or Apache Spark.
- Experience with Azure Databricks and MLflow; Azure Machine Learning experience is preferred.
- Understanding of lakehouse architecture, Delta Lake, layered data platforms, data modeling, data transformation, and analytical or ML data structures.
- Knowledge of data quality, metadata, lineage, access control, governance, and enterprise data platform integration.
- Knowledge of Git, Azure DevOps, infrastructure-as-code tools such as Terraform or Bicep, CI/CD, cloud resource management, monitoring, and cost optimization.
- Understanding of end-to-end Azure Data and AI solution architecture, including security, identity, networking, and scalable deployment patterns.
- Ability to evaluate architecture alternatives based on performance, security, maintainability, and cloud cost.
- Strong communication, analytical, collaboration, leadership, coaching, and vendor oversight abilities.
- Fluent English and Hungarian are required; fluent French and familiarity with higher education systems are advantageous.
Benefits
- Attractive compensation package, with no specific salary amount stated.
- SZÉP card cafeteria benefits.
- Private health insurance.
- Home office opportunity three times per week.
- Team-building events and a vibrant community.
- Support for professional development and training.
- Position based in Budapest and available immediately.