Years of Experience:

At least 5 - 6 years’ experience in developing, implementing and maintaining IT systems.

Role and Responsibilities:

The AI/ML Engineer supports the development and deployment of scalable and optimized artificial intelligence (AI) and machine building and implementing algorithms to extract, transform, and load large volumes of real production-ready AI/ML solutions.

Job Summary Critical Work Functions and Key Tasks:

He/She conducts model experiments, monitors performance, and troubleshoots issues to ensure stability and effectiveness in environment.
He/She is proficient in programming, scripting, and statistical methods, and familiar with the platforms used to.
The AI/ML Engineer is also expected to apply good practices in responsible AI and data governance.
He/She should have working and comply with requirements under the Personal Data Protection Act (PDPA).

Conduct research on artificial intelligence (AI)/machine learning (ML) models and algorithms:

Research and implement machine learning algorithms and tools for AI/ML model development.
Identify appropriate algorithms based on user requirements.
Select appropriate datasets and data representation methods for analysis.
Evaluate AI/ML models for production.

Build and assess AI/ML models

Develop codes to package the AI/ML models for scaling.
Develop AI/ML development pipeline and infrastructure.
Develop scalable data pipelines to extract, transform, load and integrate unstructured data from various sources.
Scale AI/ML models for production.
Support continuous improvement of AI solutions.

Deploy AI/ML models in solutions.

Test the operation and performance of the deployed models.
Identify bugs during deployment and create bug fixes to address issues.
Engage in code reviews to improve AI/ML models
Perform statistical analysis and fine tuning of the model using test results.
Prepare documentation to outline data sources, models and algorithms used and developed.
Research and implement machine learning algorithms and tools for AI/ML model development.

Requirements / Qualifications Requirements:

Bachelor’s or master’s degree in computer science, Engineering, or a related field.
Proven experience as a GenAI Engineer, with a focus on Azure and OpenAI integration. Experience with AWS and Google GenAI services is preferred.
Strong programming skills in languages such as Python and/or Java.
Experience with Azure services, including Azure Machine Learning, Azure Cognitive Services, and Azure Functions.
Familiarity with OpenAI technologies, such as GPT-3/4 and reinforcement learning frameworks.
Solid understanding of machine learning algorithms and deep learning frameworks.
Proficiency in data preprocessing, feature engineering, and model evaluation techniques.
Strong problem-solving and analytical skills
Excellent communication and collaboration abilities.
Ability to work independently and as part of a team in a fast-paced environment.

Preferred Qualifications:

Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWS AI/ML services.
Knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML.
Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.
Knowledge of containerization technologies such as Docker and Kubernetes.
Familiarity with DevOps practices and tools for CI/CD pipelines.

AI/ML Engineer