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.

Job Description The MLOps Manager role is all about leading and managing the deployment, management, maintenance and optimization of machine learning models in production environments. They are also responsible for providing guidance and mentorship to the MLOps team members in order to aid in their capability development. The MLOps Manager will also be at the forefront of collaborating with the relevant stakeholders.

DUTIES AND RESPONSIBILITIES:

The responsibilities of this position will include but will not be limited to the following:

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 the deployment of Machine Learning models into production and ensures reliability, scalability and performance. Optimize the models to make it cost effective .

Infrastructure knowledge - evaluate and select appropriate infrastructure, tools and technologies to support end-to-end machine learning lifecycle

Automation and Orchestration - develop or oversee the development of pipelines for model inference and retraining

Collaboration - collaborate with data scientists, data engineers, insighters and other stakeholders to identify improvements in the models.

Model Governance - guides the implementation of alerting system or dashboards for tracking the health, performance and reliability of models in production and ensures compliance with regulations, privacy policies and standards

Continuous Improvement - drive continuous improvement initiatives for the enhancement of deployed models and MLOps practices

KPIs:

Model Ops efficiency

Model Performance

Business realization

Cost optimization for model scoring

Turnaround time in problem resolution 

TOP 3-5 DELIVERABLES:

MLOps strategy

Model Deployment Process

Automated Workflows or Pipelines

Monitoring system or dashboards

Team development and improvement

QUALIFICATIONS:

Work Experience

Experience in machine learning, data science, or software engineering roles.

Experience in MLOps, DevOps, or similar roles, with a focus on model deployment and operationalization.

Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes).

Proven track record of managing projects and leading teams.

Level of Knowledge

Proficiency in programming languages such as Python, R, or Java.

Strong understanding of CI/CD pipelines, version control (e.g., Git), and infrastructure as code (IaC).

Deep knowledge on data privacy regulations and best practices in model governance and security.

Knowledgeable on new and emerging technologies relevant to the MLOps domain

Education

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

SKILLS:

Soft:

Project Management

Strategic Thinking & Planning

Problem-Solving & Analytical Thinking

Excellent Communication & Interpersonal Skills

Stakeholder Management & Collaboration

Hard:

Machine Learning & Data Science Principles

DevOps & Software Engineering

Cloud Platforms

Infrastructure & Automation Tools

Monitoring Tools & MLOps Frameworks

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 here

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.