Senior ML Engineer — Production ML for Manufacturing

Corning Incorporated; San Luis Potosí; Hybrid; MXN 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive benefits

Global collaboration

Learning & development

Accommodations program

Job summary

Corning is seeking a Senior Machine Learning Engineer to design, deploy, maintain, and improve robust ML systems for manufacturing and business use. This individual contributor role is based in Monterrey with regular onsite presence and hybrid flexibility.

You will build end-to-end ML pipelines, translate prototypes into scalable production solutions, and implement MLOps practices for reliability, security, and performance. Strong Python and ML framework expertise are required.

Qualifications

• 3+ years of experience in ML engineering, data engineering, software engineering, or related technical role; 3-5 years preferred.
• Strong Python proficiency and experience with ML frameworks (scikit-learn, TensorFlow, PyTorch). End-to-end ML lifecycle and MLOps concepts including CI/CD, model versioning, orchestration, monitoring, and containerization.
• Ability to influence architecture, troubleshoot complex production issues, and coach junior team members; advanced English; onsite in Monterrey at least two days per week.

Responsibilities

• Design, build, and maintain end-to-end ML pipelines from data ingestion to retraining.
• Lead translation of prototypes into scalable production solutions; contribute to APIs, batch and real-time systems.
• Implement MLOps/DevOps practices for versioning, orchestration, CI/CD, containerization, and security; mentor junior contributors.

Skills

Python

ML lifecycle

CI/CD

English proficiency

Education

Bachelor’s or Master’s in CS/Engineering/Data Science/SE

Tools

scikit-learn

TensorFlow

PyTorch

Databricks

MLflow

Kubeflow

Docker

Kubernetes

Job description

Corning is seeking a Senior Machine Learning Engineer to design, deploy, maintain, and improve robust ML systems for manufacturing and business use. This individual contributor role is based in Monterrey with regular onsite presence and hybrid flexibility.

You will build end-to-end ML pipelines, translate prototypes into scalable production solutions, and implement MLOps practices for reliability, security, and performance. Strong Python and ML framework expertise are required.