Hybrid AI Solutions Engineer for Production ML

ABB; Selangor; Hybrid; MYR 120,000 - 180,000; Full time

Job summary

ABB is seeking a skilled ML/AI engineer in Malaysia to design, develop, and deploy production-ready AI solutions across Operations, Sales, and Service. You will collaborate with data engineers, product managers, and stakeholders to build scalable ML pipelines and governance.

The role combines strong technical focus with business impact in a hybrid work model. You will lead end-to-end ML workflows, drive model performance, and communicate insights to both technical and non-technical audiences.

Qualifications

• Bachelor’s degree in a technical field; Master’s an advantage.
• Around 5 years hands-on ML/DS/AI experience in commercial environments.
• Proven ability to deploy ML models into production at scale.
• Strong Python programming with ML frameworks exposure.

Responsibilities

• Develop and deploy end-to-end ML/AI solutions across functions.
• Architect ML workflows: data prep, feature engineering, model dev, validation, deployment.
• Run POCs to validate business value and viability.
• Build scalable data pipelines and high-quality training data.
• Apply MLOps practices: versioning, CI/CD, containers, monitoring.
• Monitor production models and retrain to maintain accuracy and relevance.

Skills

Python

ML concepts

Data analysis

Communication

Education

Bachelor's degree in Computer Science or related

Master's degree in ML/AI (advantage)

Tools

AWS SageMaker

Azure ML

Google Vertex AI

TensorFlow

PyTorch

Scikit-learn

Job description

ABB is seeking a skilled ML/AI engineer in Malaysia to design, develop, and deploy production-ready AI solutions across Operations, Sales, and Service. You will collaborate with data engineers, product managers, and stakeholders to build scalable ML pipelines and governance.

The role combines strong technical focus with business impact in a hybrid work model. You will lead end-to-end ML workflows, drive model performance, and communicate insights to both technical and non-technical audiences.