I will setup mlflow and dvc for ml experiment tracking and model versioning

Losing track of ML experiments, datasets, and model versions? I'll fix that with a production-ready MLOps setup your team can actually use.

What you get:

• MLflow tracking server setup (self-hosted or cloud: AWS, GCP, or Azure)
• DVC integration for dataset and model versioning
• Model registry configuration with staging/production workflows
• Experiment logging structure (parameters, metrics, artifacts)
• Clear documentation and handover so your team runs it independently

Why me:

Level 1 seller, 8 completed orders, 5.0 ratings.

M.Sc. Software Engineering (FAST-NUCES). I specialize in MLOps tooling MLflow, DVC, Airflow, Docker, Kubernetes not generic DevOps. Clients across the US, Canada, and Europe.

How it works:

1. Free scoping call we review your current ML workflow
2. I design the tracking/versioning architecture
3. Setup, testing, and integration with your existing code
4. Documentation + live handover session

Message me before ordering so I can confirm scope and timeline for your stack.