Hire MLOps engineers in Latin America

What an MLOps engineer does

• Packages models and serves them through APIs or batch jobs.
• Builds pipelines that train, test and release models the same way every time.
• Tracks experiments, data versions and models in a registry, so any result can be reproduced.
• Monitors models in production for drift, errors and slow responses, and starts retraining when needed.
• Manages GPUs and keeps cloud cost under control.

Skills to look for

• Python, containers and Kubernetes.
• CI/CD for models and data as well as for code.
• Deep knowledge of one major cloud: AWS, Google Cloud or Azure.
• ML tooling such as MLflow, Kubeflow, SageMaker or Vertex AI.
• Monitoring and alerting, and the judgement to know which alerts matter.
• Infrastructure as code with Terraform or a similar tool.

Interview questions that show real experience

• How did you deploy the last model you put into production, and how did you roll it back when something went wrong?
• A model gets slowly worse over three months. How would you notice, and what would you do?
• How do you make a training run reproducible six months later?
• How have you reduced GPU or inference cost?

MLOps, DevOps or platform engineer?

A DevOps or platform engineer runs the infrastructure for your software. An MLOps engineer does the same for models, which adds data versions, training jobs and model quality in production. If your data scientists build models that never leave their notebooks, you need an MLOps engineer. If you are building features on top of hosted language models, an LLM engineer may be the better first hire.

Why Latin America for MLOps

Problems in production show up during your working day. Engineers in Mexico, Peru, Chile, Argentina and Brazil work within a few hours of US time, so the person who owns your models is online when your team is.

How we help

Tell us about the role. We speak with each engineer about it before we share their profile, and you receive a shortlist of vetted engineers. You only pay when you hire, and if the hire leaves within 90 days, we find a replacement for free.

Questions companies ask

Can one person cover MLOps and data engineering?

At an early stage, often yes. Look for someone who has built data pipelines and deployed models, and say in the job post that the role covers both. See hiring data engineers.

Can the engineer work as a contractor?

Yes. We recruit for contractor and full-time roles.

Do I pay anything if I do not hire?

No. You pay only when you hire someone we introduced.