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Machine Learning Engineer

2 weeks ago

Raffles, Singapore Accolite Digital Full time

JD - Enterprise Analytics - Machine Learning / Integration Engineer

Hiring Manager: Bruno Aissaoui

Who we are

Enterprise Analytics (EA) stands at the forefront of UOB's vision, aiming to establish the bank as a leader

in deploying cutting-edge Machine Learning models. Comprising a team of experts, we focus on

enhancing the bank's capabilities in supporting key areas such as Risk, Wealth, Retail, etc., with a strong

emphasis on coordination in data management, technology, and internal stakeholder collaboration.

Upholding to UOB’s core value of being enterprising, we are incredibly thrilled about strengthening this

strategic unit’s capabilities for the bank, envisioning significant progress and innovation. We firmly

believe that advanced analytics is a pivotal factor in delivering premier AI services to our stakeholders.

Your Profile

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of striking

a balance between visionary thinking and practical solutions. The ability to comprehend, inspire, and

mobilize others is crucial. A business-oriented mindset coupled with effective storytelling will drive your

success. We are looking for self-starters ready to take on responsibilities with enthusiasm.

Your Role

This Lead ML / Integration Engineer role focuses on building and integrating Generative AI and Agentic

AI solutions into enterprise environments. You will work closely with data scientists, architects, and

DevOps teams to design, implement, and optimize AI pipelines and infrastructure.

Key Responsibilities:

- Integrate AI models into production environments using containerized platforms such

as OpenShift and Kubernetes.
- Collaborate with cross-functional teams to understand AI workflows and translate them into

robust engineering solutions.
- Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant

tools.
- Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS,

Azure, GCP).
- Implement and maintain network security protocols to safeguard AI systems and data pipelines.
- Monitor and optimize system performance, reliability, and scalability.
- Support CI/CD processes and infrastructure for AI model deployment and updates.## RESTRICTED ##

Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 7+ years of experience in Machine Learning engineering or AI system integration.
- Hands-on experience with OpenShift, Docker, Kubernetes.
- Knowledge of cloud platforms (e.g. AWS, GCP) is a must-have.
- Exposure to data and network security and compliance in AI systems.
- Understanding of Generative AI and Agentic AI concepts.
- Experience with LLM prompt engineering, or RAG pipelines.
- Knowledge of API integration and microservices architecture.
- Proficiency in Python used both for ML and automation tasks
- Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
- Knowledge of Workflow Orchestrator, such as Ctrl-M
- Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
- Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana,

OpenTelemetry.

Soft Skills
- Excellent communication skills
- Attention to detail
- Strong problem-solving mindset with a can-do attitude
- Strong Organizational skills
- Visual Thinking
- Empowering delegation
- Mentorship and coaching.

Pay: $4,070.17 - $15,460.16 per month

**Benefits**:

- Health insurance

Expected Start Date: 01/08/2025