Model Ops Manager

Overview Join to apply for the Model Ops Manager role at Globe Telecom . 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 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. 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 the deployment of Machine Learning models into production and ensure 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 – guide the implementation of alerting system or dashboards for tracking the health, performance and reliability of models in production and ensure 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 Senior ity level Mid-Senior level Employment type Full-time Job function Management and Manufacturing Industries 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. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us. #J-18808-Ljbffr