We are looking for a MLOps to join us in Amsterdam . In this role, together with the data scientists, you will be responsible for streamlining the process of taking machine learning models to production, maintaining , and monitoring them. Y ou will participate in designing and building the models, data pre-processing, performance tuning of ML models , and more.
We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills. We hire people based on an evaluation of their potential and support them throughout their time in Amsterdam . Come join us!
The Team
Within ING, there is ING Analytics (INGA) - a major driving force in its digital transformation of the bank.
By creating measurable value for ING and its customers through world-class analytics products and services, INGA helps ING to become a leader in data-driven decision - making. Among others, INGA delivers call & speech analytics, generative AI in risk summarization, insights into portfolio performance, advanced ESG data insights (commercial purposes), data analytics platforms (cloud and on-premises), and many more.
A working day in the life of a Machine Le a rning Enginee r
A typical day for a machine learning engineer starts with coffee, catching up with colleagues, and drafting a plan for the coming day. After the standup, you may start analy zing algorithms to identify which of them works well with the problem you are trying to solve . For t he rest of the morning, you could experiment in J u p y ter notebook using S cikit L earn or use IDE to continue developing a class that implements a model or interfaces with the database.
After lunch, meet with the team to discuss the next iteration of the product, or go over new features that need to be implemented and discuss how to create or calculate those features. W rap up the day work ing on the monitoring tool for machine learning models .
How to succeed
Minimum Q ualifications
Bachelor’s degree or equivalent practical experience.
Excellent communication skills, capable of working collaboratively in a semi-remote, globally distributed team.
Hands-on experience building complex data pipelines (e.g., in Apache Spark).
Hands-on experience with technologies and frameworks used in ML (e.g., sklearn , MLFlow , etc.)
Knowledge of software engineering best practices (versioning, testing, documentation, etc.)
A minimum of 5 years work experience
Preferred Qualifications
Curious mindset; you are collaborative and passionate about helping others to grow and improve.
Knowledge of MLOps architecture and practices.
Experience with monitoring and observability.
Experience with deployment and provisioning automation tools and concepts, e.g., Docker, Openshift , CI/CD.
Good understanding of different data storages (e.g., RDBMS, non- SQL , and time-series databases).
Rewards and benefits
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. You can find out more about our employment conditions at Benefits in the Netherlands

Please refer the Job description for details