Machine Learning DevOps Engineer

at ING

📍 Warsaw, Poland

PLN 156,000-336,000 per year

SENIOR

✅ On-site

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Airflow @ 4 Azure @ 4 Azure DevOps @ 4 Cloud Composer @ 4 Communication @ 6 Data Science @ 6 DevOps @ 4 Fraud @ 4 GCP @ 4 GitHub @ 4 MLOps @ 4 Machine Learning @ 4 Pandas @ 3 Python @ 3 Spark @ 4 Statistics @ 6 Terraform @ 4 scikit-learn @ 3

Details

ING Hubs Poland is seeking a Machine Learning DevOps Engineer to develop platforms and implement fraud detection models within the banking sector. The role works closely with data scientists and supports the deployment and optimization of machine learning models globally across ING Group divisions.

Responsibilities

Optimize code and compute resources, including unit testing.
Schedule and distribute code on the data analytics platform.
Work with a shared model development codebase.
Assist with machine learning model development and deployment.
Collaborate with data scientists within the squad.
Perform maintenance activities.
Contribute to designing, building, and implementing banking fraud detection models.
Work within a Scrum framework.

Requirements

Experience with cloud platforms, including GCP and Azure DevOps.
Experience with GitHub, Airflow or Cloud Composer, Spark or DataProc, Terraform, and containerization.
Proficiency in data and software engineering, with a focus on distributed computing and Spark 3.5+.
Programming experience in Python and familiarity with clean coding paradigms.
Understanding of MLOps and experience with machine learning model deployment.
Familiarity with Scikit-learn, Pandas, and NumPy.
Excellent problem-solving, attention to detail, communication, and teamwork skills.
Ability to work independently and collaboratively.
English proficiency at B2 level.

Additional Qualifications

Hands-on experience with code and compute optimization, tuning, and testing.
Experience handling large datasets for fraud detection model development.
A master's degree in computer science, statistics, data science, or a related field.
Experience with additional machine learning frameworks and libraries.
Relevant certifications.
Banking-sector experience, particularly with fraud detection systems.

Team

The team cooperates with ING Group divisions in the Netherlands, Germany, Spain, Italy, Poland, and Romania. It uses a broad range of technologies and offers opportunities to experiment with machine learning technologies and techniques. The position operates within a Scrum framework.

The role naming convention in the global ING job architecture is “Engineer IV”.