Machine Learning Engineer

Corning Incorporated; San Luis Potosí; Hybrid; MXN 350,000 - 550,000; Full time

Benefits offered by this job

Competitive benefits

Global collaboration

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

Machine learning

Data science

English proficiency

Education

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

Tools

scikit-learn

TensorFlow

PyTorch

Databricks

MLflow

Docker

Kubernetes

Job description

Machine Learning Engineer

Date: Oct 5, 2026

Location: Obispado, NLE, MX, 64060

Company: Corning

Are you ready to turn machine learning ideas into reliable solutions that improve how products are made?

What is your role?

As a Machine Learning Engineer, you will work within a collaborative technical team to build, deploy, monitor, and maintain machine learning solutions that create measurable business value. You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move models from experimentation into scalable and reliable production environments. This role is based in Monterrey and requires regular onsite presence, with hybrid flexibility.

Major responsibilities and tasks of the position:

• Participate in the development and maintenance of end-to-end machine learning pipelines, including data ingestion, preprocessing, training, validation, deployment, monitoring, and retraining.
• Collaborate with data scientists and engineers to translate prototypes and experimental models into production-ready solutions.
• Support model serving through APIs, batch jobs, or real-time systems, and apply MLOps practices for versioning, orchestration, monitoring, and CI/CD.
• Troubleshoot data, model, deployment, and integration issues while maintaining clear technical documentation and participating in code reviews.

What do you need to have?

• Bachelor's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering, or a related technical field.
• 0-2 years of experience in machine learning, data science, data engineering, software engineering, or relevant hands-on academic, internship, personal, or professional projects.
• Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn, TensorFlow, or PyTorch.
• Understanding of the machine learning lifecycle and the ability to clearly explain a project, your personal contribution, the tools used, and the outcome.
• Basic familiarity with data pipelines, databases, APIs, software development practices, or workflow automation.
• Advanced technical and business English, both written and verbal.
• Ability to work onsite in Monterrey at least two days per week and support plant-based projects as needed.

What would be a plus?

• Exposure to Databricks, MLflow, Kubeflow, Docker, Kubernetes, CI/CD, or other MLOps/DevOps tools.
• Experience with manufacturing, industrial, process, plant, or production data.- A GitHub portfolio or other examples that demonstrate hands‑on technical work.

What do we offer?

• Competitive benefits above the requirements of Mexican law.
• Opportunity to work on high‑impact machine learning initiatives that support manufacturing and business transformation.
• Collaborative global environment with exposure to Data Science, IT, analytics, and manufacturing teams.
• Learning and career development in a growing technical organization.

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodation to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodations related to disability or religion, please contact us at [e-mail]