We are seeking an MLOps / DevOps Engineer with experience in cloud platforms and machine learning workflows. As part of the Digital Data Science team, you will support the development, automation, and deployment of next-generation ML models and data-driven solutions. Your work will directly impact how machine learning models are built, deployed, and scaled across production environments. You will collaborate closely with Data Scientists and Engineering teams to ensure seamless integration of ML workflows into scalable systems. This role requires a balance of technical skills, problem-solving abilities, and a proactive mindset to deliver efficient and reliable solutions. You will have the opportunity to contribute to high-impact projects for a Fortune 500 client while growing your expertise in modern MLOps practices.

Responsibilities

Building tools for automation around ML workflows orchestration and model deployments using CI/CD workflows

Automating infrastructure deployments and tool configurations using Terraform or similar IaC tools

Writing clean,



maintainable and testable code using Python, Go or other object-oriented programming languages (e.g., Java)

Troubleshooting and resolving issues related to ML workflow deployments in production environments

Generating and maintaining operational reporting pipelines using tools such as BigQuery, Looker and Tableau

Collaborating closely with Data Scientists to improve developer workflows and ensure seamless integration with tools

Working cross-functionally with general teams to support ML systems and deployments

Skills:

Hands-on experience with Vertex AI or similar platforms (e.g., Amazon SageMaker)

Understanding of ML models, model deployment, monitoring and scaling in production environments

Proficiency in Python (1-3 years of experience)

Basic experience with GCP or AWS

Experience with Kubernetes or other container orchestration platforms

Familiarity with CI/CD pipelines and infrastructure automation

Bas

📌 MLOps Engineer – Level I (Monterrey)
🏢 Confiz
📍 Monterrey