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Your Role

We are seeking an experienced Vertex AI Engineer and Cloud Delivery Lead to drive the design, deployment, and operationalisation of machine learning solutions on Google Cloud. This role bridges AI/ML engineering and cloud delivery, ensuring that models and pipelines reach production reliably, securely, and at scale.

Key Responsibilities:
- Design and implement end-to-end MLOps pipelines on Vertex AI, including data ingestion, model training, evaluation, and deployment
- Build and manage Vertex AI Pipelines (Kubeflow Pipelines) for automated model training and retraining workflows
- Deploy and manage models using Vertex AI Model Registry, Endpoints, and Batch Prediction services
- Implement feature engineering workflows using Vertex AI Feature Store




- Develop GCP-native integrations connecting Vertex AI with BigQuery, Dataflow, Cloud Storage, and Pub/Sub
- Manage infrastructure for ML workloads using Terraform, ensuring reproducible and version-controlled environments
- Configure IAM policies for Vertex AI workloads including service account governance and VPC Service Controls
- Lead cloud delivery activities: sprint planning, release management, environment promotion, and stakeholder communication
- Establish model monitoring using Vertex AI Model Monitoring for data drift and skew detection
- Collaborate with data scientists to containerise experiments and promote models through dev/staging/production
- Drive adoption of GKE for model serving workloads where custom inference infrastructure is required

Your Profile
- 4+ years of experience with GCP, including 2+ years hands-on with Vertex AI
- Strong proficiency in Python and ML frameworks (T

📌 Vertex Ai Engineer (Pune)
🏢 Capgemini
📍 Pune