What is an MLOps engineer?

Definition: An MLOps engineer builds and runs the infrastructure that takes machine learning models from experiment to production, including training pipelines, deployment and monitoring.

What an MLOps engineer does

MLOps applies DevOps practices to machine learning. The engineer automates data and training pipelines, versions models and datasets, sets up model registries, and builds the CI/CD that ships models safely. After deployment they monitor latency, cost, data drift and model quality, and set up alerts and rollback paths.

For LLM applications the work often extends to prompt and model version tracking, managing inference endpoints, controlling token spend and running automated evaluations on each release.

When a company needs one

Teams usually hire an MLOps engineer when models work in notebooks but releases are manual, fragile or slow, or when several models in production need consistent monitoring and governance.

How Ryz helps

Ryz MLOps engineers work on your team, reporting to your leads, in clouds such as AWS and Azure. Typical pricing is $7,000 to $15,000 per engineer per month, depending on seniority.

Related

• Hire MLOps engineers
• MLOps services
• LLM evaluation engineer
• LLM fine-tuning