Hybrid Junior MLOps Engineer: Pipelines & Deployment

PPG; Santiago de Querétaro; Híbrido; MXN 180.000 - 240.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Pension plan

Medical and life insurance

Descripción de la vacante

PPG is seeking an entry-level ML Engineer to design, build, and support end-to-end ML pipelines within our enterprise environment. You will contribute to model development, deployment, and operations under established ML engineering tools and standards, reporting to Data Scientist Lead.

The role is hybrid, with responsibilities across ML pipelines, deployment, validation, and documentation, suitable for early-career professionals with 1–2 years of related experience and fluent English.

Formación

• 1-2 years of related work experience in Academic projects, internships, or early professional experience supporting machine learning, data engineering, ML, Data science, CI/CD or DevOps programs.
• Fluent in English.

Responsabilidades

• Develop, test, and maintain ML pipelines and supporting components
• Help with model deployment, versioning, and monitoring under established MLOps frameworks
• Implement data preprocessing, feature engineering, and validation logic
• Debug and resolve basic issues related to model performance, pipelines, or infrastructure
• Participate in code reviews and apply feedback to improve code quality
• Maintain technical documentation for components and workflows

Conocimientos

Fluent in English

Descripción del empleo

PPG is seeking an entry-level ML Engineer to design, build, and support end-to-end ML pipelines within our enterprise environment. You will contribute to model development, deployment, and operations under established ML engineering tools and standards, reporting to Data Scientist Lead.

The role is hybrid, with responsibilities across ML pipelines, deployment, validation, and documentation, suitable for early-career professionals with 1–2 years of related experience and fluent English.