SO MLOps Integration Engineer, GMET
United Overseas Bank Open · verified Oct 22, 2026 At a glance
Mid-level ML Platform & Ops role at United Overseas Bank. Central Region · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain pipelines that train, deploy, monitor and retrain machine learning models
- Set up infrastructure for larger ML workloads using containers and cloud platforms
- Connect models to existing and new applications with data science, engineering and IT operations teams
- Automate model testing and releases, then track model performance, data drift and system health
- Resolve deployment and infrastructure problems while meeting bank security and governance rules
What you bring
- A degree in computer science, engineering, data science or another related quantitative field
- At least one year working in MLOps, DevOps or a similar role supporting machine learning systems
- Strong Python programming skills are essential
- Experience with MLOps tools, container technology and cloud platforms; familiarity with CI/CD and ML model lifecycles
Who this fits
This role suits someone who can work independently and alongside technical teams, and who communicates clearly. It is based in Singapore’s Central Region and is hybrid.
From the employer
About UOB
United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.
Job Description
We are seeking a Senior Officer MLOps Integration Engineer to join our team. This role will be crucial in bridging the gap between data science and IT operations, focusing on the seamless integration, deployment, and monitoring of machine learning models within our enterprise systems.
Job Responsibilities:**
* Design, develop, and maintain robust MLOps pipelines for model training, deployment, monitoring, and retraining.
* Implement and manage infrastructure for scalable machine learning workloads, including containerization (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP).
* Collaborate with data scientists, software engineers, and IT operations teams to ensure efficient and reliable model integration into existing and new applications.
* Develop and implement automated testing, continuous integration, and continuous deployment (CI/CD) strategies for ML models.
* Establish and maintain monitoring and alerting systems for model performance, data drift, and operational health.
* Troubleshoot and resolve issues related to ML model deployments and infrastructure.
* Ensure compliance with bank security and governance policies throughout the ML lifecycle.
* Research and implement new MLOps tools and best practices to optimize efficiency and reliability.
* Document MLOps processes, architectures, and solutions for maintainability and knowledge sharing.
Job Qualifications:**
* Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
* 1+ years of experience in MLOps, DevOps, or a similar role focused on machine learning systems.
* Strong programming skills in Python is essential.
* Proficiency with MLOps platforms and tools (e.g., MLflow, Kubeflow, Sagemaker, Azure ML, Vertex AI).
* Experience with containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
* Solid understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps).
* Familiarity with machine learning concepts, algorithms, and model lifecycle management.
* Experience with data engineering concepts and tools (e.g., SQL, Spark, Kafka).
* Excellent problem-solving skills and the ability to work independently and as part of a team.
* Strong communication and interpersonal skills.
* Experience in the financial services industry is a plus.
Additional Requirements
Be a Part of the UOB Family
UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.
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