Alex Thewsey
WW AI ML Solutions Architect - Open Source Integrations
Singapore
Summary
🤩
Rockstar🎓
Top SchoolAlex Thewsey is a WW AI/ML Solutions Architect at AWS with a decade of experience designing and operationalizing enterprise AI, specializing in integrating AWS AI services with open-source tooling. Based in Singapore, he has guided Southeast Asian customers across diverse use cases—from computer vision and forecasting to document understanding and fraud analytics—while authoring technical enablement content and hands-on workshops. A practical contributor to open-source ML examples (notably improving Amazon SageMaker semantic segmentation notebooks and migrating them to SDKv2), he blends deep engineering chops with customer-focused architecture. His background ranges from cognitive solutions and data science at IBM to embedded algorithm design early in his career, giving him a rare mix of systems-level thinking and applied research. Colleagues rely on him for scaling AI expertise across organizations and turning experimental models into production-ready platforms.
9 years of coding experience
Master of Engineering (M.Eng.), Engineering, Class 2.1, Master of Engineering (M.Eng.), Engineering, Class 2.1 at University of Cambridge
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
amazon-sagemaker10
machine-learning10
jupyter-notebook10
python10
aws9
deep-learning9
computer-vision9
semantic-segmentation8
data-science8
pytorch3
Programming languages (13)
Github contributions (5)
aws/amazon-sagemaker-examples
Nov 2020 - Sep 2021
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 5 PRs, 4 comments in 10 months
Contributions summary:Alex contributed to updating and improving an example related to semantic segmentation algorithms within the Amazon SageMaker framework. The updates involved migrating to SageMaker SDKv2, optimizing data sources, addressing CI build issues, and enhancing the example's documentation and presentation. The changes focused on the use of the fully-convolutional network (FCN) algorithm with the Pascal VOC dataset.
pythonjupyter-notebooktrainingawssagemaker
apac-ml-tfc/personalize-poc
Nov 2020 - Aug 2021
Customized Amazon Personalize PoC-in-a-Box materials
Contributions:14 commits, 4 PRs, 11 pushes in 9 months
boxpersonalizecustomizedamazonamazon-personalize
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