Artificial Intelligence Engineer

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.

Contributions to open-source GenAI or cloud service integration projects.