Senior MLOps Engineer

MLOps Engineer

Amsterdam, Netherlands (hybrid working)

Up to 107k annually + benefits

This is an opportunity to work on large scale, real time machine learning systems that directly impact millions of digital transactions. You will join a growing ML platform team focused on delivering robust, production ready solutions across payments and fraud, with strong ownership and visibility from day one.

The Company

They are a global technology organisation operating at the intersection of data, payments, and digital experiences. Their platform supports high volume, real time transactions for well known international businesses, focusing on performance, reliability, and innovation. With a strong engineering culture, they invest heavily in data and machine learning to drive continuous improvement. Teams are collaborative, fast paced, and committed to delivering meaningful impact.

The Role

You will focus on building and scaling MLOps capabilities within a production environment, supporting a range of machine learning use cases.

• Design and build scalable systems for training, deploying, and monitoring machine learning models
• Support real time and batch ML workflows across critical platform services
• Develop and scale feature store capabilities for both online and offline use cases
• Improve observability and monitoring across ML systems
• Collaborate closely with data scientists and engineers to productionise models
• Take ownership of end to end delivery of ML features and systems
• Contribute to best practices in MLOps, CI CD, and cloud infrastructure

Your Skills and Experience

• Strong commercial experience in MLOps or machine learning engineering
• High proficiency in Python for production level systems
• Experience deploying and maintaining machine learning models in production environments
• Knowledge of monitoring, observability, and system reliability
• Exposure to cloud platforms, ideally AWS
• Familiarity with ML tools and frameworks such as TensorFlow, PyTorch, Spark, or similar
• Experience with tools such as Databricks, SageMaker, Kubeflow, or equivalent platforms is beneficial
• Strong communication skills with the ability to work across technical teams
• A curious mindset and a practical approach to solving complex problems

What They Offer

• Competitive salary and benefits package
• Hybrid working model with a collaborative office environment in Amsterdam
• Opportunities to work on high impact, large scale ML systems
• Clear progression and career development within a growing team
• Supportive engineering culture with strong mentorship and ownership

How to Apply

If you are interested in this Machine Learning Ops Engineer opportunity in Amsterdam, please apply with your CV for immediate consideration.