MLOps Engineer – Data Analytics Platform

REQ-10117422

30/06/2026

IT Engineering

Warsaw, Poland

Katowice, Poland

Katowice

ING Hubs

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ING Hubs Poland is hiring!

The expected salary for this position: 9600 - 19000 PLN

The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.

We are looking for you, if you:

have good understanding of machine learning model deployment and consumption patterns

have hands-on experience with workflow orchestration tools, especially Apache Airflow (must-have)

have experience with ML lifecycle management tools such as MLflow (strongly preferred)

have 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)

have experience in building containerized components (Docker)

have experience in CI/CD and DevOps practices

have hands-on experience with data pipelines and ETL processes

have 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

Your 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

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”

The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.

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ING Recruitment team

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