Machine Learning Engineer

• Design, develop, train, and optimize machine learning models using modern frameworks;
  
  
• Build and maintain scalable data processing pipelines for data ingestion, transformation, and preparation;
  
  
• Implement and manage ML workflows using model tracking/versioning tools such as MLflow or similar;
  
  
• Create and maintain containerized environments for model deployment (e.g., Docker, Kubernetes);
  
  
• Collaborate with engineering and data science teams to integrate ML solutions into production systems;
  
  
• Monitor, evaluate, and continuously improve model and pipeline performance.
  

Requirements

• A degree in an analytical field (e.g., Computer Science, Engineering, Mathematics, Statistics, or a similar domain);
  
  
• 4+ years of experience as a Machine Learning Engineer or in a similar role;
  
  
• Strong proficiency in Python;
  
  
• Hands-on experience with ML frameworks such as Keras, PyTorch, and scikit-learn;
  
  
• Experience with MLflow or equivalent model management tools;
  
  
• Experience with PySpark and large-scale data processing;
  
  
• Experience in containerization (Docker, Kubernetes, or similar).
  
  
• Good level of English (B2/C1).
  

• Experience with Kubeflow or similar MLOps platforms.
  
  
• Knowledge of CI/CD best practices applied to machine learning pipelines.