Vertex Ai Engineer & Cloud Delivery Lead
Capgemini · Pune · onsite · Posted 59d ago
Undisclosed4–9 yrsfulltimeSourced from
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About this role
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired bya collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations
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:
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 (TensorFlow, PyTorch, Scikit-learn)
- Experience building Vertex AI Pipelines and managing model lifecycle in Vertex AI Model Registry
- Solid Terraform skills for provisioning Vertex AI, GCS, BigQuery, and associated infrastructure
- Good understanding of GCP IAM, particularly for securing ML pipelines and data access
- Experience with GCP-native development patterns and event-driven architectures
- Demonstrated cloud delivery experience including planning, execution, and stakeholder management
- Familiarity with containerisation (Docker) and GKE for model serving
What you''ll love about working here
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Skills
DockerData ingestionModel MonitoringRelease Managementaws iamMLOpsgoogle cloud platformCloud Storagefeature engineeringKubeflowbigqueryintegrationsMl PipelinesPytorchdeploymentGoogle Kubernetes EnginePythoncloudArtificial IntelligenceMachine Learning
About Capgemini
Capgemini
IT Services & Consulting
235k+
employees
1967
59 years old
Mumbai, Maharashtra
India
About
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value.
Industries
IT Services & ConsultingAnalytics & KPOBankingSoftware Product
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