About the RoleWe are looking for an Interim MLOps Engineer / Machine Learning Engineer to join their ML Engineering team. This role focuses on operationalising machine learning solutions and ensuring they are reliable, scalable, and production-ready. The ideal candidate combines a strong Software Engineering background with hands-on MLOps experience and is comfortable working across the full machine learning lifecycle, from deployment and monitoring to continuous optimisation within a collaborative engineering environment.ResponsibilitiesDeploy Machine Learning models into production environments;Build, maintain, and optimise training and inference pipelines;Design, develop, and maintain production-grade ML platforms;Integrate Machine Learning solutions into business processes;Monitor model performance, data quality, model drift, and data drift;Implement automated model validation and retraining processes;Ensure AI solutions are scalable, reliable, robust, and maintainable;Manage and optimise production environments.RequirementsStrong Software Engineering background with experience deploying ML solutions into production;Excellent understanding of the complete Machine Learning lifecycle;Hands-on experience with Python, Databricks, Apache Spark;Experience with Feature Engineering, Training and Inference Pipelines, Production Monitoring and Code Optimisation;Experience building and maintaining scalable production ML platforms;What We OfferAn interim position (freelance) Location: Rotterdam, with a hybrid working model;

Sourced from LinkedIn. Relocantly aggregates public job postings; apply on the original site.

ML Ops Engineer