Mid/Senior MLOps Engineer (GCP / Azure / Kubernetes) 100% Remote

Salary: 20,000–30,000 PLN net + VAT per month

About the role

Contribute to MLOps systems supporting real cloud and data platforms in enterprise-scale environments.

What You Will Work On

• Turning model experiments into production-ready services
• Building deployment and automation processes
• Setting up monitoring and observability for model-serving environments
• Improving the reliability, scalability and maintainability of MLOps platforms
• Working with Kubernetes in cloud environments
• Supporting governance and security requirements

What We Expect

Must-Have

• 3+ years of commercial experience in MLOps, ML Engineering, DevOps, Data Engineering, cloud or backend engineering, including production ML workloads
• Experience with Azure or Google Cloud
• Strong Python skills, including testing, packaging and dependency management
• Hands-on experience with Docker and Kubernetes
• Practical knowledge of CI/CD, Git workflows and deployment automation
• Understanding of the ML lifecycle: tracking, versioning, deployment, inference, monitoring and rollback
• Basic knowledge of ML concepts, including metrics, reproducibility and data or model drift
• English at B2+ level and communicative Polish

Nice-to-Have

• Experience with Vertex AI, Azure Machine Learning, Databricks or Snowflake
• Knowledge of MLflow, Kubeflow or similar platforms
• Experience with Airflow, Prefect or Dagster
• Infrastructure-as-Code experience, preferably Terraform or Bicep
• Experience with Helm and Kubernetes deployment automation
• Experience with batch or real-time inference and model serving
• Knowledge of model monitoring, drift detection and automated retraining
• Experience with Prometheus, Grafana or cloud monitoring tools
• Understanding of cloud security fundamentals
• Relevant cloud, Kubernetes or DevOps certifications

Example Projects

An end-to-end ML platform for a global pharmaceutical company operating more than 30 manufacturing facilities centralized real-time IoT and production data in the cloud. Using Databricks, Azure ML and Vertex AI, the platform supported models recommending optimal PLC configurations to manufacturing engineers, helping identify quality issues earlier, reduce defective medicine batches and improve production efficiency.

A Databricks-based analytics engine categorized bank transactions and applied complex business rules to account data. The solution enabled advanced creditworthiness and credit-risk assessment based on customers’ transactional behavior in a highly regulated and secure banking environment with strict data-protection and governance requirements.

What We Offer

• 20,000–30,000 PLN net + VAT per month on B2B
• 20 days off
• 100% remote work
• Training budget and support in cloud certifications
• Work with a specialized team of around 60 data experts
• Projects in real enterprise cloud and data environments
• Private medical care, sports package, English lessons and team integrations

Recruitment Process

• Soft Skills Interview (30 min): short discussion about communication and teamwork
• Technical Conversation (60 min): deep-dive discussion about MLOps, cloud, Kubernetes and past projects
• Final decision and offer