- Developing and refining AI prompts to improve the clarity, relevance, and effectiveness of AI-generated responses.- Writing and implementing code to enhance AI capabilities, enabling dynamic interactions and tailored responses for specific use cases.- Testing AI outputs, analyzing weaknesses or inconsistencies, and iterating on prompts and underlying code to continually improve AI accuracy and power.

- Orchestrated complex data transformation workflows using Databricks and Delta Live Tables for seamless integration with downstream model development.- Automated end-to-end data engineering processes across multi-cloud environments (AWS and GCP) by implementing Terraform for scalable infrastructure deployment.

- Developed cutting-edge generative models that transform text inputs into high-quality images and videos. These models utilize advanced techniques to capture intricate details and maintain contextual relevance, ensuring that the outputs are not only visually appealing but also coherent and aligned with user expectations.- Established a robust CI/CD pipeline to automate the processes of testing, deployment, and scaling for machine learning models. This infrastructure enhances development efficiency and allows for rapid iteration and integration, ensuring that updates and improvements can be deployed seamlessly into the cloud environment without disruption.- Utilized diverse datasets to effectively train the models, drawing on rich and varied examples to enhance their understanding and generation capabilities. By leveraging powerful hardware, the project ensures optimal performance, enabling the generation of multimedia content that meets the demands of real-time applications and user interactions. This comprehensive approach enhances both the scalability and reliability of the generative AI system.

- Conducted in-depth research on neural networks, focusing on improving modelinterpretability and transparency. Engineered web solutions and worked on knowledgesystems to ensure data accuracy and integrity.- Developed a virtual knowledge framework as a modern alternative to traditionaldatabases, incorporating advanced features like concept similarity measurement.

- Managed end-to-end data flow, extracting raw data from SQL databases, staging in blob storage, and consolidating with third-party tables in Azure Databricks.- Delivered customer insights through Azure Synapse Analytics, optimizing data processes for Kiatnakin Phatra Financial Group.