AI/ML Engineer

Monterrey
Montevideo
Remote.AR
Remote.Colombia
Rosario

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Client

Our client is the leading airline in Latin America, operating the largest network of destinations, frequencies, and fleet in the region. The company is driving innovation through advanced AI/ML initiatives, with a strong focus on next-generation GenAI solutions.

Project overview

You will join a strategic initiative within the Emantto domain, contributing to the acceleration of LATAM’s AI portfolio across multiple touchpoints. The role combines ML/AI engineering with strong software, cloud, and infrastructure skills. You will build and operate GenAI-driven data products, support domain teams, and act as a facilitator of LATAM’s Data & AI Platform.

Position overview

We are looking for an AI/ML Engineer with solid knowledge in Cloud, IaC, CI/CD, and SWE best practices, focused on designing, building, and operationalizing GenAI-based solutions.

Responsibilities

Develop and deliver data products and AI/GenAI solutions within domain teams.
Act as a facilitator of LATAM’s Data & AI Platform, enabling adoption and accelerating delivery across squads.
Build, deploy, and operate GenAI/ML models in scalable, production-ready environments.
Manage infrastructure topics for environments and AI/ML products, including observability, performance, and reliability.
Contribute to CI/CD pipelines, IaC practices, and platform automation.
Collaborate with cross-functional teams (SWE, Data, MLOps, DevOps) to ensure high engineering standards.
Support experimentation frameworks and internal tools for GenAI model development and evaluation.

Requirements

Experience with GCP (or a similar cloud provider such as AWS/Azure).
Experience with Terraform or other IaC tools.
Strong knowledge of Python.
Backend engineering experience (APIs, services) and GenAI OR ML/MLOps experience (Airflow, MLflow, pipelines, monitoring.
Solid understanding of CI/CD, containerization (Docker), and SWE best practices.
Familiarity with model deployment, model serving, and operating ML/AI systems in production.

Nice to have

Experience with observability, incident response, or platform operations.

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