ml-ops-engineer

No direct malware or deliberate data theft is evident in the supplied code. The principal risks are software and model supply-chain integrity: mutable container images, unpinned CI actions, execution of repository-controlled scripts, unverified MLflow/XGBoost artifacts, and automatic production deployment. Pin images and actions by immutable digest or commit, verify signed artifacts, restrict model-loading formats and registry permissions, validate paths and parameters, and add explicit promotion approvals and rollback controls.