AI Solutions Engineer

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

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This position reports to:

Service Business Process Manager

Your role and responsibilities

In this role, you will develop and deploy end-to-end AI and machine learning solutions that address complex business challenges across Operations, Sales, and Service functions. This role combines technical expertise in ML/AI with business acumen to translate customer needs into scalable, production-ready AI solutions. The engineer works closely with data engineers, product managers, and business stakeholders to architect, build, test, and optimize AI models while ensuring solution quality, governance, and measurable business impact.

The work model for this role is: #LI-Hybrid

You will be mainly accountable for:

• Designing, developing, and deploying machine learning models and AI solutions to solve business challenges in operations, maintenance, forecasting, and process optimization.
• Architecting end-to-end ML workflows, including data preparation, feature engineering, model development, validation, and production deployment.
• Conducting exploratory data analysis, feasibility assessments, and proof-of-concept (POC) initiatives to evaluate business value and technical viability.
• Collaborating with data engineers and cross-functional teams to build scalable data pipelines and ensure high-quality training datasets.
• Applying ML engineering and MLOps best practices, including model versioning, CI/CD, containerization, monitoring, governance, and documentation.
• Monitoring model performance in production, address model drift, and implement retraining strategies to maintain accuracy and business relevance.
• Communicating AI/ML insights to technical and non-technical stakeholders, contribute to engineering standards, and drive adoption of emerging AI technologies and best practices.

Qualifications for the role

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related technical discipline; Master’s degree in Machine Learning, Data Science, Artificial Intelligence, or a related field is an advantage.
• Around 5 years of hands‑on experience in Machine Learning, Data Science, or AI solution development within a commercial or enterprise environment.
• Demonstrated success in designing, developing, and deploying machine learning models into production environments at scale.
• Strong programming skills in Python, with practical experience using ML frameworks and libraries such as Scikit-learn, TensorFlow, and PyTorch.
• Experience working with cloud‑based machine learning platforms, including AWS SageMaker, Azure Machine Learning, or Google Vertex AI.
• Solid understanding of MLOps, model lifecycle management, and deployment pipelines, with exposure to business‑driven AI use cases such as predictive maintenance, forecasting, optimization, or intelligent automation.

What’s in it for you?

We want you to bring your full self to work—your ideas, your energy, your ambition. You’ll have the tools and freedom to grow your skills, shape your path, and take on challenges that matter. Here, your work creates impact you can see and feel, every day.

More about us

ABB’s Service Division partners with our customers to improve the availability, reliability, predictability and sustainability of electrical products and installations. The Division’s extensive service portfolio offers product care, modernization, and advisory services to improve performance, extend equipment lifetime and deliver new levels of operational and sustainable efficiency. We help customers keep resources in use for as long as possible, extracting the maximum value from them, and then recovering and regenerating products and materials at the end of their useful life.

Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That’s why we welcome people from all backgrounds and experiences.

Ready to make an impact?