In this role you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers) where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
In this role you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers) where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
As an Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering storage and both batch and real-time processing.
Collaborating closely with diverse teams you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer you'll tackle obstacles related to database integration and untangle complex unstructured data sets.
We are looking for a MLOps Data Engineer to design implement and maintain productive Machine Learning pipelines on Google Cloud Platform (GCP) . This professional will ensure that AI models developed by Data Science teams are efficiently deployed automated and monitored ensuring scalability performance and data governance.
ResponsibilitiesDesign and maintain production-grade ML pipelines in GCP.
Implement automation for model deployment and monitoring.
Work with containers in GKE and automation using Cloud Build and CI/CD.
Support data scientists in transitioning prototypes into production.
Ensure best practices in version control testing and documentation.
Mandatory skillsStrong experience in Python and ML/Deep Learning libraries (TensorFlow PyTorch Scikit-learn).
Proficiency in GCP services : Vertex AI BigQuery Pub/Sub Dataflow.
Experience with Docker and Kubernetes (GKE) .
Knowledge of CI/CD and automated testing.
2–3 years of experience in ML or Data Engineering with hands-on practice in GCP.