MLOps & Infrastructure

Full ML lifecycle management with experiment tracking, model registry, containerized serving, and Kubernetes orchestration.

Automate ML model testing, validation, and deployment pipelines using GitHub Actions with data and model versioning.

Provision reproducible ML infrastructure on any cloud using Terraform and orchestrate ML workflows with Kubeflow Pipelines.