What you'll do
- Design, develop, and integrate machine learning models into production environments
- Build and maintain data pipelines and model training workflows
- Develop and enhance MLOps infrastructure for model lifecycle management, automation, and monitoring
- Write production-grade Python code and build APIs or services for ML models
- Monitor, evaluate, and retrain models to maintain accuracy and performance
- Collaborate with data engineers, annotation teams, software developers, and product managers
- Participate in code reviews, documentation, and engineering best-practice definition
Key requirements
- 5+ years' experience
- Python, machine learning libraries, and machine learning model development and deployment
- MLOps tools and practices, including MLflow, Kubeflow, and Airflow
- Data pipelines and model training workflows
- Cloud platforms and API and service development
- Model monitoring and retraining
- People management, team leadership, and analytical thinking and problem-solving
- Computer Science / Mathematics / Statistics
Benefits
- You’ll be part of a growing AI team within a well-established organization transforming its services through technology.
- You’ll work on end-to-end ML systems with real business impact across automation and document intelligence domains.
- Gross monthly salary is €3,500–€4,000.
About the job
Our client is a leading Greek company specializing in information management and digital transformation. It provides solutions for document management, intelligent data processing, and secure information storage. Through advanced technologies and automation, the company helps organizations optimize workflows, ensure compliance, and improve operational efficiency across industries.
Language Requirement: English, Greek
Minimum Years of Experience: 5
Key Responsibilities
Design, develop, and integrate machine learning models into production environments.
Build and maintain data pipelines and model training workflows to ensure reliable and automated processes.
Develop and enhance the company’s MLOps infrastructure for model lifecycle management, automation, and monitoring.
Write production-grade Python code and build APIs or services that expose ML models to business applications.
Continuously monitor, evaluate, and retrain models to maintain accuracy and performance.
Collaborate with data engineers, annotation teams, software developers, and product managers to align solutions with business objectives.
Participate in code reviews, documentation, and the definition of engineering best practices.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related discipline.
At least 5 years of hands-on experience developing and deploying machine learning models.
Proven people management or team leadership experience.
Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).Solid understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Airflow).
Working knowledge of cloud platforms such as AWS, GCP, or Azure.
Excellent analytical thinking, problem-solving, and communication skills.
Fluent in English, both written and spoken.
Nice-to-Have Skills
Experience with document understanding, OCR, or NLP models.
Familiarity with containerization (Docker, Kubernetes) and CI/CD for ML pipelines.
Exposure to data governance, model monitoring, or AI observability tools.
Salary (Ind.): 3500-4000 € / Per month Gross
What They Offer
You’ll be part of a growing AI team within a well-established organization that is transforming its services through technology.
You’ll work on end-to-end ML systems, from data ingestion to deployment, with real business impact across automation and document intelligence domains.
If you’re passionate about building scalable ML products and want to see your models running in production, this is the right environment for you.

