Hybrid Machine Learning Engineer: From Prototypes to Production

Corning Incorporated; San Luis Potosí; Híbrido; MXN 350 000 - 550 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive benefits

Global collaboration

Resumo da oferta

Corning is seeking a Machine Learning Engineer to turn ML ideas into reliable production solutions. The role collaborates with data scientists, analytics leaders, IT, and manufacturing teams to move models from experiments to scalable systems.

You will work onsite in Monterrey with hybrid flexibility, contributing to end-to-end ML pipelines and model serving while ensuring robust documentation and CI/CD practices.

Qualificações

• Bachelor's degree in a related technical field.
• 0-2 years of hands-on ML, data engineering, or software projects.
• Strong Python foundation; experience with ML libraries.
• Ability to explain project contributions, tools used, and outcomes clearly.
• Familiarity with data pipelines, databases, APIs, and CI/CD basics.

Responsabilidades

• Develop and maintain end-to-end ML pipelines from data ingestion to deployment.
• Collaborate with data scientists and engineers to productionize models.
• Support model serving via APIs, batch jobs, or real-time systems with MLOps practices.
• Troubleshoot data, model, and deployment issues and maintain clear technical docs.

Conhecimentos

Python

Machine learning

Data science

English proficiency

Formação académica

Bachelor's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering

Ferramentas

scikit-learn

TensorFlow

PyTorch

Databricks

MLflow

Docker

Kubernetes

Descrição da oferta de emprego

Corning is seeking a Machine Learning Engineer to turn ML ideas into reliable production solutions. The role collaborates with data scientists, analytics leaders, IT, and manufacturing teams to move models from experiments to scalable systems.

You will work onsite in Monterrey with hybrid flexibility, contributing to end-to-end ML pipelines and model serving while ensuring robust documentation and CI/CD practices.