Machine Learning DevOps Engineer

About the role

ING Hubs Poland is hiring! The expected salary for: expert position: 13 000 - 28 000 PLN The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations. We are a dynamic and rapidly growing tech company, seeking a talented Machine Learning DevOps Engineer to join our team. The successful candidate will be responsible for developing platform and implementing fraud detection models within the banking sector. We are looking for you if: You have experience with cloud platforms: GCP, Azure (DevOps). You have experience with GitHub, Airflow/Cloud Composer, Spark/DataProc, Terraform, containerization. You are proficient in data & software engineering with a special focus on distributed computing (Spark 3.5+). You are familiar with 'Clean Coding' paradigms and have programming experience in Python. You understand ML Ops and have been involved in ML model deployment. You are familiar with model development frameworks (Scikit-learn, Pandas, NumPy). You possess excellent problem-solving skills, attention to detail, and the ability to work both independently and collaboratively. You have excellent communication and teamwork skills. You'll get extra points for: Hands-on experience with code/compute optimization and tuning testing. Proven capability in handling large data sets for developing fraud detection models. Master's degree in computer science, statistics, data science or a related field. Experience with other machine learning frameworks and libraries. Certifications in relevant fields. Experience in the banking sector, particularly with fraud detection systems. Your responsibilities: Code/compute optimizations & (unit) testing. Scheduling & distributing code on our data analytics platform. Working with shared model development codebase. Assist in model development/deployment. Collaboration with data scientists in squad. Maintenance. English level: B2 Information about the squad: Are you interested in becoming an integral part of a pioneering team that cooperates in designing, building, and implementing models in the realm of banking fraud detection? We employ a wide range of technologies. Our team enjoys the flexibility to experiment with cutting-edge technologies and techniques in the field of machine learning. Our clientele includes various divisions of the ING Group, spanning countries such as the Netherlands, Germany, Spain, Italy, Poland, and Romania. By joining us, you will have the opportunity to implement and optimize machine learning models on a global scale, crafting innovative solutions for customers in diverse countries. We are committed to continuous professional development and offer every team member the chance to expand their skills and pursue their interests in a dynamic and collaborative environment. Our team operates within a Scrum framework, and we're currently seeking an additional ML DevOps Engineer who will enrich our team. The role naming convention in the global ING job architecture will be “Engineer IV” We’re a global bank with a strong European base, and our more than 60,000 colleagues serve around 38 million customers and corporate clients in over 40 countries. Joining ING means working with friendly and collaborative people towards making a positive impact on people and planet. We believe in empowering the people around us and our customers to stay a step ahead. Working here means having the autonomy to drive progress, helping to create superior customer value and contributing to our ambition of putting sustainability at the heart of everything we do. Here, we’re more than just a workplace – we’re a community of innovators, problem-solvers, and forward-thinkers, dedicated to making a real impact. Whether you’re just starting your career or seeking the next big challenge, we have opportunities that will inspire and push you to grow. Your future at ING starts with one application. Ready to join? We’ve got plenty of opportunities to match your skills and aspirations! Use the filters below the search bar – like location and job type – to help you find the perfect fit. Start exploring now and discover where your next career move could take you!

Posted Oct 11, 2026