MLOps Lead: Deploy, Scale & Optimize Production ML

Globe Telecom; Manila; On-site; PHP 2,000,000 - 3,200,000; Full time

Job summary

Globe Telecom, Inc. is seeking an experienced MLOps Manager to lead deployment, management, and optimization of machine learning models in production. You will guide a team, shape strategy, and drive end-to-end ML lifecycle—from model inference pipelines to governance and continuous improvement.

You will partner with data scientists, engineers and business stakeholders to ensure reliable, scalable, and cost-efficient ML solutions that align with Globe’s aims and regulatory standards.

Qualifications

• Minimum of 5 years of experience in machine learning, data science, or software engineering roles.
• At least 2–3 years of experience in MLOps, DevOps, or similar roles focused on deployment and operationalization.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
• Strong communication and collaboration across cross-functional teams.
• Proficiency in Python, R, or Java.

Responsibilities

• Lead and mentor the MLOps team to deliver scalable ML deployment and maintenance.
• Develop and execute MLOps strategy aligned with Globe objectives and governance.
• Oversee model deployment into production with reliability, scalability and performance.
• Build pipelines for inference and retraining; optimize costs and infrastructure.
• Collaborate with data scientists, data engineers, and stakeholders to improve models.

Skills

MLOps

Team Leadership

Model Deployment

CI/CD

Python

R

Java

Cloud Platforms

Kubernetes

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

Docker

Kubernetes

Git

Terraform

CI/CD Tools

Job description

Globe Telecom, Inc. is seeking an experienced MLOps Manager to lead deployment, management, and optimization of machine learning models in production. You will guide a team, shape strategy, and drive end-to-end ML lifecycle—from model inference pipelines to governance and continuous improvement.

You will partner with data scientists, engineers and business stakeholders to ensure reliable, scalable, and cost-efficient ML solutions that align with Globe’s aims and regulatory standards.