Data Engineer
Azure ML Engineer
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Azure ML Engineer / ML Ops Specialist
Join a team where knowledge is a hot commodity and where we love what we do!
Company
About Galileo Global Education
Galileo Global Education
is a leading international higher education group focused on innovation, creativity, arts and culture. Our goal is to help students build strong career prospects by combining high-quality learning environments, digital platforms, industry expertise and global networks.
Galileo Global Education HUB
in Hungary supports the Group’s schools, business units and support functions with dedicated IT services, contributing to both digital transformation projects and daily IT operations.
About The Role
We are looking for a hands-on ML Engineer / MLOps Specialist to support the design, implementation and operation of machine learning solutions within a Microsoft Azure and Databricks environment.
The role combines machine learning engineering, MLOps and a solid understanding of modern data architecture. The successful candidate will work closely with internal data teams and external vendor partners to ensure that ML solutions are scalable, secure, maintainable and cost-efficient.
Key Responsibilities
- Design and implement end-to-end machine learning pipelines on Azure and Databricks.
- Operationalise ML models, including deployment, monitoring, retraining and version management.
- Build and maintain MLOps processes using CI/CD, infrastructure as code and automated testing.
- Define suitable Azure resources, Databricks compute and deployment patterns with a strong focus on cost optimisation.
- Integrate ML solutions with lakehouse-based data platforms and existing data pipelines.
- Collaborate with data engineers, architects, business stakeholders and external vendors.
- Review vendor solutions and ensure alignment with internal architecture, security and operational standards.
- Contribute to reusable ML platform components, technical standards and documentation.
What We Are Looking For
- Strong practical experience in ML engineering and MLOps, including deploying, operating, monitoring, retraining and versioning ML models in production.
- Strong Python skills, with practical experience in PySpark or Apache Spark.
- Experience with Azure Databricks, MLflow and preferably Azure Machine Learning.
- Good understanding of lakehouse architecture, Delta Lake, layered data platforms, data modelling, data transformation and designing data structures for analytical and ML use cases.
- Basic knowledge of data quality, metadata, lineage, access-control concepts, governance and integration of ML workloads with enterprise data platforms.
- Knowledge of CI/CD, Git, Azure DevOps and infrastructure-as-code tools such as Terraform or Bicep.
- Experience with cloud resource management, monitoring and cost optimisation.
- Good understanding of end-to-end Azure Data/AI solution architecture, including security, identity, networking and scalable deployment patterns.
- Ability to evaluate architecture alternatives considering performance, security, maintainability and cloud cost.
- Experience collaborating with and technically overseeing external vendors, including architecture and solution reviews.
- Strong communication and interpersonal skills, including listening to clients, working in cross-functional teams, and clear verbal and written communication.
- Fluent English and Hungarian.
- Great numerical and analytical skills.
- Leadership and coaching mindset, team spirit, and ability to foster inclusive, supportive team dynamics.
- Readiness to work in the niche field of higher education, where service and experience are paramount.
- Service-oriented and autonomous approach: responsiveness to client requests, flexibility, versatility, daily proactivity and thirst for learning.
- Commitment to standards and consistency: insists on consistent engineering practices and documentation without creating unnecessary bureaucracy.
Nice to have
- Fluent French would be a plus
- Familiarity with higher education systems and processes is a plus.
Compensation & Perks
An attractive package designed for top talent:
- A salary that values your expertise and impact
- SZÉP card cafeteria benefits
- Private health insurance
- Home office opportunity 3 times a week
- A vibrant community with great team-building events
- Support for professional development and training
Application
The position is based in Budapest, available immediately. Please apply with your English CV.
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