Role and Responsibilities:

The AI/ML Engineer supports the development anddeployment of scalable and optimized artificial intelligence (AI) and machinebuilding and implementing algorithms to extract, transform, and load largevolumes of real production-ready AI/ML solutions.

Job Summary Critical Work Functions and Key Tasks:

• He/She conducts modelexperiments, monitors performance, and troubleshoots issues to ensure stabilityand effectiveness in environment.

• He/She is proficient inprogramming, scripting, and statistical methods, and familiar with theplatforms used to.

• The AI/ML Engineer is alsoexpected to apply good practices in responsible AI and data governance.

• He/She should have working andcomply with requirements under the Personal Data Protection Act (PDPA).

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

• Research and implement machinelearning algorithms and tools for AI/ML model development.

• Identify appropriate algorithmsbased on user requirements.

• Select appropriate datasets anddata representation methods for analysis.

• Evaluate AI/ML models forproduction.

• Build and assess AI/ML models

• Develop codes to package theAI/ML models for scaling.

• Develop AI/ML developmentpipeline and infrastructure.

• Develop scalable data pipelinesto extract, transform, load and integrate unstructured data from varioussources.

• Scale AI/ML models forproduction.

• Support continuous improvementof AI solutions.

• Deploy AI/ML models insolutions.

• Test the operation andperformance of the deployed models.

• Identify bugs during deploymentand create bug fixes to address issues.

• Engage in code reviews toimprove AI/ML models

• Perform statistical analysis andfine tuning of the model using test results.

• Prepare documentation to outlinedata sources, models and algorithms used and developed.

• Research and implement machinelearning algorithms and tools for AI/ML model development.

Requirements / Qualifications Requirements:

• Bachelor’s or master’s degree incomputer science, Engineering, or a related field.

• Proven experience as a GenAIEngineer, with a focus on Azure and OpenAI integration.

• Experience with AWS and GoogleGenAI services is preferred.

• Strong programming skills inlanguages such as Python and/or Java.

• Experience with Azure services,including Azure Machine Learning, Azure Cognitive Services, and AzureFunctions.

• Familiarity with OpenAItechnologies, such as GPT-3/4 and reinforcement learning frameworks.

• Solid understanding of machinelearning algorithms and deep learning frameworks.

• Proficiency in datapreprocessing, feature engineering, and model evaluation techniques.

• Strong problem-solving andanalytical skills

• Excellent communication andcollaboration abilities.

• Ability to work independentlyand 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 Cloudservices, including Google Cloud AI Platform, Google Cloud Functions, andGoogle Cloud AutoML.

• Experience with cloud-baseddeployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.

• Knowledge of containerizationtechnologies such as Docker and Kubernetes.

• Familiarity with DevOpspractices and tools for CI/CD pipelines.

• Contributions to open-sourceGenAI or cloud service integration projects.