As an AI Specialized Cloud Solution Architect (CSA) and trusted advisor to top Azure customers at Microsoft, I am responsible for empowering our customers by unlocking their full potential with AI. I work closely with customers, partners, and internal teams to understand their business needs and challenges, and design and implement innovative and scalable solutions using Microsoft's cloud-based Data and AI services. I also mentor and coach other technical professionals, share best practices and insights, and contribute to the development of new products and features. I am passionate about empowering organizations to achieve more.
- Diverse knowledge of providing effective business strategies, data modeling and business modeling
- Extensive experience in a variety of industries including telecommunication, oil & gas, manufacturing, and e-commerce etc.
- Good analytical skills and the ability to quickly assess data and investigate transaction data using statistical approach
- Experience in predictive analytics, advanced statistical modelling, and data visualization for big data
- Ability to translate research data into actionable information and offer an insight to business issues and opportunities
- Strong problem solving and troubleshooting skills and highly attentive to detail
- Ability to prioritize workload in an interrupt-driven environment with minimal or no supervision
- Communicating with clients and internal team frequently and effectively to ensure that the objectives of the project are being fulfilled
- ποΈ AIML Infra: Multi-node distributed training, model serving, evaluation-driven LLMOps
- π Research to Production: Bridging experimentation with scalable, reliable, and safe deployment, focusing on robust infrastructure, prompt engineering, guardrails, rigorous testing (hallucinations, bias), data governance, monitoring (cost, latency), and continuous learning
- π§βπ» AIML: Fine-tuning, Traditional ML/Data Science, Computer Vision
- βοΈ Cloud + AI Platforms: Azure AI, Hugging Face, Databricks
- Akepanidtaworn, Klakow and Akepanidtaworn, Korkrid, GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms. IMF Working Paper No. 2025/252, Available at SSRN: https://ssrn.com/abstract=5933712
- Korkrid Kyle Akepanidtaworn (2025). Document Generation and Summarization Accelerator | by Korkrid Kyle Akepanidtaworn | CodeX | Medium
- Korkrid Kyle Akepanidtaworn (2025). How I Built a High-Performing Data Science Team with AutoGen Studio (AGS) | by Korkrid Kyle Akepanidtaworn | Apr, 2025 | Medium
- Korkrid Kyle Akepanidtaworn, He Zhang (2024). Fine-Tuning GPTs on Azure with a User-Friendly Dashboard | by Korkrid Kyle Akepanidtaworn | Medium
