MLOps Engineer - Remote Work

Role Overview

BairesDev is seeking an experienced MLOps Engineer to design, build, and maintain infrastructure and processes for machine learning model lifecycle management. The role focuses on CI/CD for ML models, monitoring, automation, versioning, and ensuring scalable, reliable ML infrastructure in production.

Responsibilities

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

Requirements

• 4+ years of 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 pipelines, model monitoring, and ML lifecycle management.
• Experience with cloud platforms and containerization (Kubernetes, Docker).
• Experience with relational and non-relational databases.
• Ability to evaluate and choose MLOps tools/frameworks with understanding of trade-offs.
• Advanced English.

Nice to Have

• Experience integrating ML solutions into enterprise systems and setting up end-to-end production MLOps practices.