MLOps Engineer – Data Analytics Platform

Details

ING Hubs Poland is hiring!

The expected salary for this position: 9600 - 19000 PLN.

Responsibilities

• Developing and managing workflow orchestration using Airflow (core responsibility)
• Supporting and improving model lifecycle management using MLflow (tracking, registry, reproducibility)
• Actively contributing to the migration of the ML Batch platform from on-premise (IPC) to Google Cloud Platform (GCP)
• Refactoring and adapting ML pipelines to run efficiently in cloud-native environments
• Developing and improving templates for productionizing ML solutions
• Integrating ML pipelines with CI/CD pipelines for automated deployments
• Ensuring scalability, reliability, and reproducibility of ML workloads
• Troubleshooting and optimizing pipelines to improve performance and stability
• Participating in on-call support to maintain platform reliability
• Collaborating with stakeholders to deliver scalable, secure, and cost-efficient solutions

Requirements

• Good understanding of machine learning model deployment and consumption patterns
• Hands-on experience with workflow orchestration tools, especially Apache Airflow (must-have)
• Experience with ML lifecycle management tools such as MLflow (strongly preferred)
• Hands-on experience working with Google Cloud Platform (GCP) in the context of data or ML pipelines (e.g. BigQuery, Vertex AI, Cloud Storage or similar)
• Experience in building containerized components (Docker)
• Experience in CI/CD and DevOps practices
• Hands-on experience with data pipelines and ETL processes
• Hands-on experience with monitoring, logging and troubleshooting ML pipelines
• Can clearly express ideas and collaborate effectively with data scientists and engineers
• Speak English at B2 level or above

You’ll get extra points for

• Strong experience with Airflow-based workflow design and optimization
• Experience with Vertex AI in GCP
• Experience with Spark or distributed batch data processing
• Familiarity with Kedro or similar pipeline frameworks
• Experience with Kubernetes or distributed environments

Information about the squad

ML-Batch is a robust, scalable, and efficient platform provided by DAP. The goal of our team is to empower users by providing them with an easy-to-use platform for designing & implementing batch processing, ETL, and machine learning pipelines. By leveraging cutting-edge tools like Airflow & MLFlow and by adhering to MLOps methodology, we aim to facilitate seamless, high-performance data workflows, ensuring that our users can execute their data-driven tasks reliably and efficiently. MLOps practices ensure continuous integration, deployment, and monitoring, enabling a streamlined and collaborative approach to machine learning operations.

As an MLOps Engineer, you will:

• Help migrate ML pipelines and workflows to GCP
• Contribute to shaping the target ML platform architecture
• Work with technologies such as Airflow (orchestration), MLflow (model lifecycle), and Spark (data processing)

You will join a multinational multi-cultural team delivering scalable, secure, and automated solutions that enable data scientists across ING to build high-impact products.

You will work with modern technologies, solve complex problems, and help shape the future of ING’s data ecosystem in a cloud-first environment.

The role naming convention in the global ING job architecture will be “Engineer III.”