Monterrey ML Engineer - End-to-End ML & MLOps

Corning Incorporated; Monterrey; Híbrido; MXN 240.000 - 360.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive benefits

Global collaboration

Career development

Hybrid work model

Descripción de la vacante

Corning Incorporated in Monterrey is seeking a Machine Learning Engineer to build, deploy, monitor, and maintain ML solutions that deliver measurable business value. The role collaborates with data scientists, IT, analytics, and manufacturing to move models from experimentation into production, with regular onsite presence and hybrid flexibility.

Responsibilities include end-to-end ML pipelines, production-ready models, API or real-time serving, and clear technical documentation.

Formación

• Bachelor's degree in a technical field.
• 0-2 years of ML or data engineering experience.
• Strong Python and ML library experience (scikit-learn, TensorFlow, PyTorch).
• Ability to explain project contributions, tools used, and outcomes.
• Basic knowledge of data pipelines, databases, APIs.
• Advanced technical and business English.
• Ability to work onsite in Monterrey at least two days per week.

Responsabilidades

• Develop and maintain end-to-end ML pipelines, including data ingestion, preprocessing, training, validation, deployment, monitoring, and retraining.
• Collaborate with data scientists and engineers to translate prototypes into production-ready solutions.
• Support model serving through APIs, batch jobs, or real-time systems with MLOps practices.
• Troubleshoot data, model, deployment, and integration issues with clear technical documentation.

Conocimientos

Python

ML lifecycle

Data pipelines

English (advanced)

Team collaboration

Educación

Bachelor's degree in a technical field

Herramientas

Databricks

MLflow

Kubeflow

Docker

Kubernetes

CI/CD

Descripción del empleo

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]