Machine Learning Operations Manager

Globe Telecom, Inc.; Philippines; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Globe Telecom, Inc. is seeking an experienced MLOps Manager to lead the deployment and maintenance of machine learning models. The role includes team leadership, strategic planning, and collaboration with cross-functional teams to ensure model performance and compliance with data privacy regulations.

Ideal candidates have 5+ years in machine learning and MLOps with strong communication and programming skills. This position provides an opportunity to drive innovation and continuous improvement in MLOps practices at Globe.

Qualifications

• Minimum of 5 years of experience in machine learning, data science, or software engineering.
• At least 2–3 years in MLOps, DevOps focused on model deployment.
• Proven ability to manage projects and lead teams.
• Knowledge of data privacy regulations and model governance.
• Willingness to learn new technologies in MLOps.

Responsibilities

• Lead and mentor team members in MLOps.
• Develop and execute the MLOps strategy.
• Oversee deployment of machine learning models.
• Evaluate infrastructure and tools for ML lifecycle.
• Develop pipelines for model inference and retraining.
• Collaborate with cross-functional teams.
• Implement alerting systems for model performance.
• Drive initiatives for enhancing MLOps practices.

Skills

Machine learning

Data science

Software engineering

Project management

Team leadership

Communication skills

Problem-solving

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field

Tools

Python

R

Java

AWS

Azure

Google Cloud

Docker

Kubernetes

CI/CD pipelines

Git

Job description

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

The MLOps Manager role is all about leading and managing the deployment, maintenance and optimization of machine learning models in production environments.

Responsibilities

• Team Leadership – provide mentorship, guidance and support to team members.
• Strategic Planning – develop and execute MLOps strategy aligned with Globe’s objectives.
• Model Deployment and Management – oversee deployment of machine learning models into production and ensure reliability, scalability, and performance, optimizing cost effectiveness.
• Infrastructure – evaluate and select appropriate infrastructure, tools, and technologies to support end‑to‑end ML lifecycle.
• Automation & Orchestration – develop or oversee pipelines for model inference and retraining.
• Collaboration – work with data scientists, data engineers, insight teams, and other stakeholders to identify improvements.
• Model Governance – implement alerting systems or dashboards for tracking model health, performance and reliability, ensuring compliance with regulations, privacy policies, and standards.
• Continuous Improvement – drive initiatives for enhancing deployed models and MLOps practices.

Requirements

• 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 model deployment and operationalization.
• Proven track record of managing projects and leading teams.
• Knowledge of data privacy regulations and best practices in model governance and security.
• Willingness to continuously learn and adapt to new technologies and methodologies in MLOps.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Soft Skills

• Excellent communication and interpersonal skills, with the ability to collaborate with cross‑functional teams and translate technical concepts into business terms.
• Strong problem‑solving abilities and analytical thinking.

Hard Skills

• Proficiency in programming languages such as Python, R, or Java.
• Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes).
• Strong understanding of CI/CD pipelines, version control (e.g., Git), and infrastructure as code (IaC).

Equal Opportunity Employer

Globe’s hiring process promotes equal opportunity to applicants. Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants. Globe’s Diversity, Equity and Inclusion Policy Commitment can be accessed.