Senior AI Engineer & MLOps Lead

DKSH Management Ltd.; Malaysia; On-site; MYR 150,000 - 210,000; Full time

Job summary

DKSH Management Ltd. in Malaysia seeks an AI Engineer (MLOps) to engineer, deploy, and operate production-grade AI/ML solutions at scale across the group.

This role sits at the intersection of AI, software engineering, and cloud platforms to accelerate value from AI investments. You will design and maintain MLOps pipelines, deploy on Microsoft Azure, implement CI/CD and model lifecycle management, monitor data drift, and collaborate with data scientists and engineers to productionize analytics

Qualifications

• Minimum 5 years of experience in AI engineering, MLOps or related roles.
• Hands-on experience deploying AI/ML in production.
• Proficiency in Python and software engineering best practices.
• Experience with Databricks and MLflow for deployment and lifecycle management.
• Experience with Azure ML, Azure DevOps, Docker, and Kubernetes.
• Ability to work in agile teams and communicate with technical and non-technical stakeholders.

Responsibilities

• Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models.
• Engineer scalable deployment architectures across cloud environments, especially Azure.
• Implement CI/CD, versioning, rollback, and lifecycle management.
• Monitor models for data drift and performance, with remediation strategies.
• Collaborate with data scientists and engineers to productionize analytics.
• Develop reusable components and templates to accelerate AI delivery.
• Integrate AI models into enterprise systems via APIs.

Skills

Python programming

MLOps

Cloud platforms

CI/CD automation

Stakeholder communication

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Tools

Databricks

MLflow

Azure ML

Azure DevOps

Docker

Kubernetes

Job description

DKSH Management Ltd. in Malaysia seeks an AI Engineer (MLOps) to engineer, deploy, and operate production-grade AI/ML solutions at scale across the group.

This role sits at the intersection of AI, software engineering, and cloud platforms to accelerate value from AI investments. You will design and maintain MLOps pipelines, deploy on Microsoft Azure, implement CI/CD and model lifecycle management, monitor data drift, and collaborate with data scientists and engineers to productionize analytics