Samson Tan is a Staff Research Scientist in the Bay Area with nine years of experience advancing NLP and LLM pretraining, robustness, tokenization, multimodality, and evaluation at organizations including Reddit and Amazon. He combines rigorous academic training (PhD, NUS) with production-savvy engineering—owning end-to-end tokenizer pipelines, speeding up decoding by 2700x in a bugfix, and leading cross-org scaling-law experiments that reduced pretraining time. At AWS he helped ship Amazon Titan tokenizers and built metrics and red-teaming tooling later used in Nova production; at Reddit he now leads pretraining science for platform-native LLMs. He is equally comfortable designing statistically sound evaluation frameworks and writing clean, scalable code, and prefers working in collaborative, kind teams. An active open-source contributor, his work spans NLP augmentation, plotting test coverage in matplotlib, and core tensor ops in PySyft, reflecting a rare blend of research publication pedigree and hands-on implementation. Colleagues describe him as curious, creative, and both scientifically and operationally fluent.
9 years of coding experience
1 year of employment as a software developer
Diploma with Merit, Digital Visual Effects, Diploma with Merit, Digital Visual Effects at Nanyang Polytechnic
Semester abroad, Computer Science, Linguistics, Entrepreneurship, Semester abroad, Computer Science, Linguistics, Entrepreneurship at The University of British Columbia
Honours College, Honours College at NUS University Scholars Programme
Doctor of Philosophy, Computer Science, Doctor of Philosophy, Computer Science at National University of Singapore
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:
ML Engineer
Contributions:67 reviews, 15 commits, 1 PR in 1 month
Contributions summary:Samson primarily contributed to the implementation and refactoring of natural language transformations within the `nl-augmenter` repository. They added new perturbation methods focused on English inflectional variations, including question-specific transformations. The user modified existing code to generate multiple perturbed outputs and refactored code for efficiency and maintainability.
This is the project website for the TEAMMATES feedback management tool for education
Role in this project:
Full-stack Developer
Contributions:12 commits, 42 PRs, 17 pushes in 3 months
Contributions summary:Samson made several contributions to the TEAMMATES feedback management tool, primarily focusing on both front-end and back-end changes. Their work included updating the UI and data display related to feedback entries, specifically modifying the submission count and presentation on the index page. They also refactored code and modified testing configurations related to instructor feedback result pages. Furthermore, the user improved the status messages given to the user and refactored code structure and improved performance.
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