Description
The Mid-Level Data MLOps Engineer will operationalise, scale, and maintain machine learning models for retail initiatives such as demand forecasting, inventory optimisation, and customer loyalty. The role covers end-to-end ML lifecycle management on Google Cloud Platform, including Vertex AI ML Pipelines, Apache Airflow, Terraform, Jenkins, Docker, BigQuery, Dataflow, model deployment, monitoring, and CI/CD. It requires 3–5 years of production MLOps, DevOps, or machine learning engineering experience and is hybrid, with three days per week at the head office.
