MLOps EngineerAmsterdam, 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 CompanyThey 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 RoleYou 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 modelsSupport real time and batch ML workflows across critical platform servicesDevelop and scale feature store capabilities for both online and offline use casesImprove observability and monitoring across ML systemsCollaborate closely with data scientists and engineers to productionise modelsTake ownership of end to end delivery of ML features and systemsContribute to best practices in MLOps, CI CD, and cloud infrastructureYour Skills and ExperienceStrong commercial experience in MLOps or machine learning engineeringHigh proficiency in Python for production level systemsExperience deploying and maintaining machine learning models in production environmentsKnowledge of monitoring, observability, and system reliabilityExposure to cloud platforms, ideally AWSFamiliarity with ML tools and frameworks such as TensorFlow, PyTorch, Spark, or similarExperience with tools such as Databricks, SageMaker, Kubeflow, or equivalent platforms is beneficialStrong communication skills with the ability to work across technical teamsA curious mindset and a practical approach to solving complex problemsWhat They OfferCompetitive salary and benefits packageHybrid working model with a collaborative office environment in AmsterdamOpportunities to work on high impact, large scale ML systemsClear progression and career development within a growing teamSupportive engineering culture with strong mentorship and ownershipHow to ApplyIf you are interested in this Machine Learning Ops Engineer opportunity in Amsterdam, please apply with your CV for immediate consideration.

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Senior MLOps Engineer