MLOps Engineer

Responsibilities

• Enable the reliable, scalable, and efficient deployment of AI and machine learning solutions across enterprise environments.
• Build reusable frameworks, automation tools, and platforms for scalable machine learning systems and data-driven applications.
• Operationalize and support production-grade machine learning models, including model lifecycle management.
• Collaborate with Data Scientists, Data Engineers, Architects, and client stakeholders.
• Develop and maintain automated testing and deployment processes across development, QA, and production environments.

Requirements

• At least 5 years of overall experience in Data Analytics.
• At least 4 years of experience in MLOps, ML Engineering, Software Engineering, or Data Engineering, including deployment and support of production-grade machine learning solutions.
• Experience building scalable machine learning systems and data-driven products with cross-functional teams.
• Strong proficiency in Python, SQL, and Databricks.
• Experience with MLOps, DevOps practices, automation, deployment pipelines, version control, and model lifecycle management.
• Strong software engineering skills, including object-oriented programming, multiple programming languages, and development, QA, and production environments.
• Proficiency in Python and experience with common data analytics packages.
• Fluent English.

Benefits

• Work on meaningful technology projects addressing real-world challenges.
• Continuous learning and exposure to cloud, MLOps, automation, and emerging AI technologies at enterprise scale.
• Work in an environment focused on sustainability, inclusion, and digital equity.
• The role can be performed from any state of Mexico.