Sr. Machine Learning Engineer

Corning Inc.; Monterrey; Hybrid; MXN 700,000 - 900,000; Full time

Benefits offered by this job

Competitive benefits

Global collaboration

Career development opportunities

Job summary

Corning Inc. in Monterrey seeks a Senior Machine Learning Engineer to design, deploy, and maintain production-grade ML systems that boost manufacturing performance.

This role is based in Monterrey with regular onsite presence and hybrid flexibility, offering opportunities to influence architecture, MLOps practices, and technical standards while collaborating with data scientists, IT, analytics, and manufacturing teams.

Qualifications

• Bachelor's or Master's degree in a technical field with 3+ years in ML/data/engineering.
• Strong Python and ML framework experience; production deployment知.
• Ability to influence architecture and coach teammates without direct reports.
• Excellent English; onsite in Monterrey at least two days a week.

Responsibilities

• Design, build, and maintain end-to-end ML pipelines including ingestion, training, deployment, monitoring, and retraining.
• Lead translation of prototypes into scalable production solutions and shape architecture for APIs and real-time systems.
• Implement MLOps/DevOps practices for versioning, CI/CD, orchestration, security, and reliability.
• Mentor junior contributors, perform code reviews, and collaborate with data scientists, IT, analytics, and manufacturing teams.

Skills

Python programming

ML lifecycle & MLOps

CI/CD & DevOps

System troubleshooting

Education

Bachelor's or Master's degree in a relevant technical field

Tools

scikit-learn

TensorFlow

PyTorch

Databricks

MLflow

Kubeflow

Docker

Kubernetes

Job description

Are you ready to lead the technical delivery of production-grade machine learning solutions that can transform manufacturing performance?

What is your role?

As a Senior Machine Learning Engineer, you will design, deploy, maintain, and improve robust machine learning systems that support manufacturing and other business functions. You will help translate data science prototypes into secure, scalable, and production-ready solutions while influencing architecture, MLOps practices, and technical standards. This is an individual contributor role based in Monterrey with regular onsite presence and hybrid flexibility.

Major responsibilities and tasks of the position:

• Design, build, and maintain end-to-end machine learning pipelines covering data ingestion, preprocessing, training, validation, deployment, model serving, monitoring, troubleshooting, and retraining.
• Lead the translation of prototypes into scalable production solutions and contribute to architecture and technology decisions for APIs, batch processing, and real-time systems.
• Implement MLOps and DevOps practices for model versioning, orchestration, CI/CD, containerization, security, data privacy, and production reliability.
• Guide junior contributors, lead code reviews and technical documentation, and partner with data scientists, IT, analytics, and manufacturing stakeholders to resolve complex production issues.

What do you need to have?

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering, or a related technical field.- At least 3 years of relevant experience in machine learning engineering, data engineering, software engineering, or a related technical role; 3-5 years is preferred.- Proven hands-on experience deploying and supporting machine learning models or systems in production environments.
• Strong Python proficiency and experience with machine learning frameworks or libraries such as scikit-learn, TensorFlow, or PyTorch.- Hands-on understanding of the end-to-end ML lifecycle and MLOps/DevOps concepts, including CI/CD, model versioning, orchestration, monitoring, and containerization.
• Ability to influence architecture and design decisions, troubleshoot complex production issues, and coach or guide less-experienced team members without direct reports.
• Advanced technical and business English, plus the ability to work onsite in Monterrey at least two days per week and support plant-based projects as needed.

What would be a plus?

• Experience with Databricks, MLflow, Kubeflow, Docker, Kubernetes, cloud or on-premise deployment, and enterprise systems integration.- Experience deploying ML solutions in manufacturing, industrial, quality, defect-reduction, or production-optimization environments.- Experience with APIs, model serving infrastructure, relational or non-relational databases, distributed computing, security, and data privacy.

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]