Senior Machine Learning Engineer

In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking a highly experienced Senior Machine Learning Engineer to join a remote development team. The role focuses on designing, deploying, and maintaining scalable machine learning solutions in production environments, with a strong emphasis on MLOps practices and ML lifecycle management using MLflow.

The candidate will collaborate closely with data scientists, data engineers, architects, and business stakeholders to deliver reliable, production-grade ML systems.

• Type of project: IT Services
• Budget: 130-150 PLN net /h- b2b
• Project length: long term
• Only candidates with citizenship in the European Union and residence in Poland

• Design, develop,and deploy machine learning models for production environments
• Implement and manage MLflow for experiment tracking, model versioning, and model deployment
• Optimize ML pipelines for performance, scalability, reliability, and cost efficiency
• Implement end-to-end ML pipelines covering training, validation, deployment, monitoring, and retraining
• Apply MLOps best practices to ensure scalability, reproducibility, and operational stability
• Collaborate with data scientists to operationalize models and improve model performance
• Work closely with data engineers to integrate ML solutions with data pipelines and data platforms
• Build and maintain containerized ML applications using Docker and Kubernetes
• Implement CI/CD pipelines for automated testing, deployment, and monitoring of ML models
• Monitor model performance, data drift, and system health; perform root cause analysis when issues arise
• Ensure security, compliance,and best practices across cloud-based ML deployments
• Minimum 8+ years" experience in machine learning engineering or related roles
• Strong proficiency in Python and modern machine learning frameworks (Tensor Flow, PyTorch, Scikit-learn)
• Hands-on experience with MLflow for model lifecycle management in production environments
• Solid understanding of MLOps principles, including CI/CD, containerization, and orchestration
• Experience deploying and operating ML workloads on cloud platforms (AWS, Azure, or GCP)
• Good knowledge of data engineering concepts and tools such as Spark and Airflow
• Strong problem-solving skills and ability to work in complex, distributed environments
• Excellent verbal and written communication skills in English

• Full-time job agreement based on b2b and employment contract
• Private medical care with dental care (covering 70% of costs) + rehabilitation package. Family package option possible
• Multisport card (also for an accompanying person)

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