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
Job Summary
As a DevOps Engineer at United Overseas Bank Ltd, you will play a critical role in designing, implementing, and maintaining robust and scalable infrastructure and pipelines for our machine learning initiatives. You will bridge the gap between development and operations, ensuring seamless integration, deployment, and monitoring of ML models and applications in a secure and efficient manner.
Job Responsibilities
- Design, build, and maintain CI/CD pipelines specifically tailored for machine learning models and applications, including automated testing, model versioning, and deployment strategies.
- Implement and manage infrastructure as code (IaC) solutions using tools like Terraform or CloudFormation to provision and configure cloud resources (AWS, Azure, GCP) for ML workloads.
- Collaborate with Data Scientists, ML Engineers, and Software Developers to understand their infrastructure needs and translate them into scalable and reliable solutions.
- Monitor the performance and health of ML systems, establish alerting mechanisms, and troubleshoot production issues related to infrastructure, deployments, and model serving.
- Optimize ML infrastructure for cost-efficiency, performance, and security, leveraging containerization (Docker, Kubernetes) and serverless technologies.
- Develop and maintain documentation for DevOps processes, tools, and infrastructure configurations.
- Promote best practices for security, reliability, and scalability within the ML development lifecycle.
- Evaluate and integrate new technologies and tools to enhance the ML DevOps ecosystem.
Job Requirements
- Bachelor's degree in Computer Science, Engineering, or a related technical field.
- 4+ years of experience in a DevOps, SRE, or MLOps role.
- Strong proficiency in at least one major cloud platform (AWS, Azure, or GCP), including experience with compute, storage, networking, and security services.
- Extensive experience with CI/CD tools (e.g., Jenkins, GitLab CI, Azure DevOps, GitHub Actions).
- Demonstrated expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes).
- Solid understanding of infrastructure as code (IaC) principles and tools (e.g., Terraform, CloudFormation, Ansible).
- Proficiency in scripting languages such as Python or Bash.
- Familiarity with machine learning concepts, MLOps principles, and experience deploying ML models into production.
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
- Strong problem-solving skills, with the ability to diagnose and resolve complex technical issues.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- Experience working in a regulated industry, such as financial services, is a plus.
Additional Requirements
Develop, Engage, Execute, Role Type (GTO), StrategiseBe 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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UOB Singapore Office
80 Raffles Place, Singapore, 048624


