Sr. Staff Engineer, Machine Learning

Corning Incorporated; Reynosa; Vor Ort; MXN 900.000 - 1.300.000; Vollzeit

Zusammenfassung

Corning Incorporated in Reynosa, Mexico, seeks a Senior Machine Learning Engineer to design, deploy, and maintain robust ML systems across manufacturing, supply chain, and technology functions.

You will build end-to-end pipelines, productionize models, and manage serving infrastructure, while ensuring security, scalability, and compliance. A strong background in Python, ML frameworks, and MLOps is required.

Qualifikationen

• Bachelor’s or Master’s degree in CS, Engineering, Data Science, or related field.
• 3-5 years of experience in ML engineering, data engineering, or software engineering.
• Hands-on Python and ML frameworks like scikit-learn, TensorFlow, PyTorch; Databricks preferred.
• Experience deploying ML models to production (cloud or on-prem).
• Familiar with MLOps tools (MLflow, Kubeflow), DevOps, and containerization (Docker, Kubernetes).
• Strong API development, data workflow automation, and distributed computing skills.
• Experience with relational and non-relational databases and data pipelines.
• Excellent problem-solving, communication, and teamwork.
• Fluent in technical and business English.

Aufgaben

• Design, develop, and maintain end-to-end ML pipelines from ingestion to retraining.
• Collaborate with data scientists to productionize models.
• Implement and manage model serving infrastructure (APIs, batch, real-time).
• Utilize MLOps for versioning, orchestration, monitoring, CI/CD.
• Troubleshoot data flows, model performance, deployment, and integration.
• Ensure security, data privacy, and compliance in ML solutions.
• Maintain documentation of pipelines and systems.
• Lead code reviews and promote technical excellence.

Kenntnisse

Python

ML frameworks

MLOps

APIs

Data pipelines

Distributed computing

Databases

English

Ausbildung

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

Tools

Docker

Kubernetes

MLflow

Kubeflow

Databricks

Jobbeschreibung

Position Overview:The Senior Machine Learning Engineer is responsible for building, deploying, and maintaining robust machine learning systems that drive business value across manufacturing, supply chain, commercial, and technology functions. This role works closely with data scientists, analytics leaders, and IT to operationalize models, automate data pipelines, and ensure scalable, reliable, and secure machine learning solutions.

Key Responsibilities:

• Design, develop, and maintain end-to-end machine learning pipelines, including data ingestion, preprocessing, model training, validation, deployment, monitoring, and retraining.
• Collaborate with data scientists to translate prototypes and experimental models into production-ready solutions.
• Implement and manage model serving infrastructure (APIs, batch jobs, real-time systems) that meet business requirements for performance and scalability.
• Leverage MLOps tools and best practices for model versioning, orchestration, monitoring, and CI/CD automation.
• Troubleshoot and resolve issues related to data flows, model performance, deployment, and integration with enterprise systems.
• Ensure security, data privacy, and compliance within all deployed machine learning solutions.
• Maintain clear documentation of pipelines, systems, and troubleshooting processes.
• Lead code reviews and contribute to a culture of technical excellence and continuous improvement.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
• 3-5 years of experience in machine learning engineering, data engineering, or software engineering.
• Hands-on proficiency with Python and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Databricks experience preferred.
• Practical experience with building and deploying ML models into production environments (cloud or on-premise).
• Familiarity with MLOps tools (e.g., MLflow, Kubeflow), DevOps practices, and containerization (Docker, Kubernetes).
• Strong skills in API development, data workflow automation, and distributed computing concepts.
• Experience working with relational and non-relational databases and data pipeline tools.
• Excellent problem-solving, communication, and teamwork skills.
• Must be fluent in technical and business English (both written and verbal)

Personal Attributes:

• Detail-oriented, analytical, and proactive in troubleshooting and optimizing systems.
• Collaborative team player who values knowledge sharing and continuous learning.
• Adaptable and enthusiastic about working with rapidly evolving technologies and business needs.