senior-ml-engineer
Production deployment patterns for your ML models.
What it does
Guides implementation of model deployments, monitoring pipelines, and LLM integrations for production applications.
When to use it
Use for production model deployment, MLOps infrastructure, performance and drift monitoring, RAG pipelines, or reliable LLM API integration.
How to use it
It changes how the agent implements production ML systems by prescribing deployment, monitoring, and LLM integration workflows.
What you provide
- An existing project
Good to know
- may misreport its own work
What you need · 2
The model deployment workflow uses Docker to package the model and its dependencies.
The bundled deployment, monitoring, and RAG tools are Python scripts; the deployment script specifies python3.
Access · 3
This skill
LLM provider pricing pages
Reads current LLM pricing
staging environment
Deploys models to staging