About ASML
At ASML they like to make the impossible possible. Their lithography technology – which uses light to print tiny patterns on silicon – is fundamental to mass producing semiconductor chips. With it, the world’s top chipmakers are creating better performing, cheaper chips.
Together with Xccelerated, an initiative within the Xebia Group with focus on the growth of Data, Cloud & AI competences, we are enabling talented people to become an authority in their field.
In collaboration with ASML we are working with the Data Hub team, in specific the predictive maintenance team, where the amount of data is growing rapidly. This maintenance team consists of two talented teams of Data engineers, MLOPS engineers and data scientist. They work every day on innovative data and software challenges and for this team we are searching for the brightest minds on the planet to help us achieve their mission.
About the role
You will join the Predictive Maintenance team as a MLOPS/Data engineer, and they need you to bring it to the next level.
You will join the Innovation Hub team for Metrology and Machine Control (MX). This innovation hub consists of four newly formed teams, and they need you to bring it to the next level and bring their Cloud and Software strategy to life.
As a MLOPS/Data engineer at ASML, you will:
Develop, test and deploy scalable and re-usable data engineering pipelines in GCP;
Deploy ML models in collaboration with Data scientists and supporting them by converting algorithms and models into production solutions;
Work with containerization technologies like Kubernetes, Kubeflow and Docker;
Create and maintain CI/CD pipelines in GCP; Take charge of the realization of the MLOps strategy of the department;
Challenge the organization to maintain a healthy balance between state-of-the-art technology, performance, and stability.
This is you
From a personal perspective, you are customer focused and have a strong can-do mentality. You focus on results, have a desire to complete challenging tasks and learn while doing. You communicate clearly with Data scientist, ML and Data engineers.
Next to this, you have:
A Technical Education background and some years of experience in the ML & Data engineer field;
Experience in software development and strong coding skills in Python and Pyspark;
Experience in creating pipelines (ETL, Kubeflow, Airflow) and deploying them;
Experience with a cloud stack.