GCP MLOps Engineer

About the Role :

We are seeking a hands-on Machine Learning Engineer who will build, deploy and operationalise ML solutions using GCP and Vertex AI. You will partner with data scientists, data engineers, product teams, and cloud infrastructure teams to deliver scalable, production-ready ML systems that drive business impact.

Key Responsibilities :

• Design and build ML pipelines : data ingestion, feature engineering, model training, evaluation, deployment, monitoring.
• Use Vertex AI services such as CustomTraining, AutoML, Vertex AI Pipelines, Model Registry, Feature Store for end-to-end ML lifecycle.
• Leverage GCP services like BigQuery, Cloud Storage (GCS), Dataflow, Pub / Sub, Cloud Functions, etc., to support ML workflows.
• Deploy trained models as endpoints (online / batch inference) and set up monitoring for model drift, performance metrics, version control.
• Apply best-practices in MLOps : CI / CD for ML, containerisation (Docker), orchestration (Kubernetes / GKE or equivalent), infrastructure as code (Terraform / Deployment Manager).
• Work with cross-functional teams to translate business requirements into ML solutions, document architectures and decisions, ensure security / governance / compliance.

Required Skills & Experience :

Nice to Have :