Vertex AI Engineer & Cloud Delivery Lead
Tasks
- Build Vertex AI Pipelines
- Configure IAM policies
- Containerize experiments and promote models
- Deploy and manage models
- Design end-to-end MLOps pipelines
- Develop GCP native integrations
- Drive adoption of GKE for model serving
- Establish model monitoring
- Implement feature engineering workflows
- Lead cloud delivery activities
- Manage ML infrastructure with Terraform
Perks/Benefits
- N/A
Skills/Tech-stack
AI Model Monitoring | AI Pipelines | AI endpoints | Batch Prediction | BigQuery | Cloud Storage | Cloud deployment | Cloud platform | Dataflow | Docker | Environment promotion | Feature Store | GKE | Google Cloud | Google Cloud Platform | IAM | Kubeflow Pipelines | Kubernetes | MLOps | Model Monitoring | Model Registry | PubSub | PyTorch | Python | Release Management | Scikit-learn | Service Controls | Service accounts | Sprint Planning | TensorFlow | Terraform | VPC Service Controls | Vertex AI | Vertex AI Endpoints | Vertex AI Feature Store | Vertex AI Model Monitoring | Vertex AI Model Registry | Vertex AI pipelines
Education
N/A
Roles
AI Engineer | Cloud Delivery Lead | Cloud) | Delivery Lead | Engineer | Lead | Vertex AI Engineer
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