We’re looking for a skilled and motivated MLOps Engineer to join our software division and contribute to building and maintaining robust infrastructure for AI and Big Data systems.

About the Role:

• Design, develop, and manage infrastructure for deploying and monitoring machine learning models
• Build and maintain Big Data infrastructure using widely adopted tools
• Develop and manage CI/CD/CT pipelines for model training, testing, and deployment
• Develop automation tools for data preparation, feature engineering, and model training workflows
• Implement version control and model management practices for traceability and reproducibility
• Mentor and support engineers and data specialists in best practices for MLOps

Qualifications

• Strong proficiency in Python
• Hands-on experience with DevOps tools: Docker, Podman, Kubernetes, Jenkins, Terraform, Ansible
• Practical experience in CI/CD with Git-based systems (GitHub/GitLab, Azure DevOps)
• Familiarity with data storage systems (SQL, NoSQL, Data Lakehouse)
• Knowledge of ML libraries (TensorFlow, PyTorch, scikit-learn) – advantage
• Experience with AI/Big Data infrastructure – advantage
• Background in cloud platforms (GCP, AWS, Azure) and managing ML cloud resources – advantage
• Familiarity with MLOps tools (ClearML, Kubeflow, MLflow) – advantage