DevOps and MLOps Engineer
Automate the delivery. Keep intelligence performing.
DevOps and MLOps Engineers create the systems and automated workflows that move software and machine learning models from development into reliable real-world use. They help teams release faster, monitor performance and keep applications and AI systems secure, scalable and dependable.
- High Demand Across Cloud and AI-Enabled Organisations
- Critical Engineering Role Connecting Development, Deployment & Operations
- Global Opportunities Across Software, Cloud & AI Teams
- Real-World Impact Delivering Reliable Digital Systems at Scale
What does a DevOps and MLOps Engineer do?
-
Automate software delivery
Create continuous integration and deployment workflows that allow teams to test and release software efficiently.
-
Deploy machine learning models
Move trained models into production environments where they can support applications, services and business processes.
-
Manage cloud infrastructure
Configure and maintain the platforms, containers and services required to run software and AI workloads.
-
Monitor system and model performance
Track reliability, speed, errors, resource use and model behaviour after deployment.
-
Improve operational resilience
Introduce automation, security controls and recovery processes that reduce downtime and support consistent performance.
Career Pathways
-
1
Master Programming and Infrastructure Fundamentals
Develop strong foundations in software development, operating systems, networking, cloud computing and version control.
-
2
Build Automation and Deployment Skills
Learn to create delivery pipelines, manage containers and automate infrastructure configuration.
-
3
Operate Software and Machine Learning Systems
Deploy applications and models, monitor performance and manage updates across production environments.
-
4
Lead Platform and MLOps Engineering
Guide engineering teams, improve deployment standards and manage complex cloud and AI operations.
-
5
Architect Enterprise Delivery and AI Operations
Direct organisation-wide platform strategy, automation, governance, resilience and model lifecycle management.
Areas You Can Specialise In
- Continuous Integration and Deployment
- Machine Learning Operations
- Cloud Platform Engineering
- Infrastructure as Code
- Container Orchestration
- Site Reliability Engineering
Where Our Graduates Work
- Technology Companies
- Financial Institutions
- Cloud Service Providers
- Government Agencies
- Healthcare Organisations
- Professional Services Firms
- AI Start-Ups
- Digital Transformation Consultancies
Real Careers. Real Impact.
- Supporting Real-World AI Deployment Singapore is moving from AI experimentation towards the deployment of production-grade systems across major industries. In 2026, a new AI Foundry announced plans to recruit professionals including AI and Machine Learning Engineers, full-stack developers and DevOps Engineers for live enterprise projects in financial services and precision health.
- Powering Enterprise-Scale Adoption Singapore’s National AI Impact Programme will support 10,000 enterprises over three years as they integrate AI into business processes. DevOps and MLOps Engineers help organisations move these solutions into secure, scalable and maintainable operating environments.
- Future Ready Singapore will upskill 40,000 technology professionals and final-year students over the next three years, with new programmes covering AI fluency, software engineering and agentic systems. As software and AI become more deeply connected, professionals who can automate delivery, monitor models and maintain reliable platforms will become increasingly important.
Ready to engineer your future in DevOps and MLOps?
Let our Future Advisors guide your journey.