MLOps Architect - AI Platform & Pipeline Ops

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 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) Bonus: experience in BPS / regulated domains with compliance-aware deployment"