MLOps Engineer - Remote Work

Role Overview

BairesDev is seeking an MLOps Engineer to design, build, and maintain the infrastructure and processes for machine learning model lifecycle management. You will help productionize ML systems by owning the CI/CD workflows, monitoring, automation, and governance practices that keep models reliable and scalable.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for machine learning models.
• Automate model deployment, monitoring, retraining, and overall lifecycle management.
• Build and manage ML infrastructure with a focus on scalability, performance, and reliability.
• Develop tools for model versioning, reproducibility, and governance.
• Collaborate with data scientists, ML engineers, and DevOps teams to integrate ML into enterprise systems.
• Monitor model performance and implement automated feedback loops for continuous improvement.
• Establish and maintain MLOps best practices and standards.
• Stay current with MLOps tools, frameworks, and industry practices.

Requirements

• 4+ years experience in MLOps, DevOps, or ML infrastructure.
• Strong software architecture background.
• Strong understanding of system security.
• In-depth knowledge of performance optimization and automation.
• Experience with CI/CD, model monitoring, and ML lifecycle management.
• Proficiency with cloud platforms and containerization: Kubernetes and Docker.
• Experience with relational and non-relational databases.
• Ability to choose appropriate MLOps tools/frameworks and understand trade-offs.
• Advanced English.

Nice-to-Haves

• Not explicitly stated (position emphasizes staying current with emerging MLOps practices).