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.
