Build and maintain ML pipelines for training, validation, deployment, and monitoring
Implement CI / CD for ML artifacts, including data versioning and model registries
Monitor model performance and drift; trigger retraining workflows as needed
Manage infrastructure (cloud, containerized, on-prem) for high-availability AI services
Collaborate with data, ML, and ops teams to deliver frictionless MLOps lifecycle
Required Skills :
Strong knowledge of MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI)
Proficiency in Python, Bash, Docker, and Kubernetes
Familiarity with cloud infra (AWS / GCP / Azure) and IaC (Terraform, CloudFormation)
Experience in model monitoring, logging, and alerting
Bonus : experience in BPS / regulated domains with compliance-aware deployment"
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Ai Platform Architect • Bengaluru, Karnataka, India
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