Tuan Nguyen
Lead Member Of Technical Staff at Salesforce
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolTuan Nguyen is a Lead Member of Technical Staff at Salesforce with a decade of experience building production ML platforms, AutoML pipelines, and RAG/agentic search applications. He blends strong statistical foundations from a Swarthmore math/stats background with hands-on engineering in Scala, Spark, Python, and JAX to move probabilistic research into scalable systems. An active open-source contributor, he’s helped extend notable projects like TransmogrifAI and JAX/TensorFlow Probability—adding model insight tooling, distributions, and numerical linear algebra primitives that improve robustness and interpretability. Colleagues rely on him for untangling flaky tests, improving feature analysis, and shipping loss-function enhancements that make models more reliable in practice. Based in Seattle, he brings a rare combination of academic rigor (statistical paleontology and bioinformatics research) and pragmatic platform-building experience to complex ML problems.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Arts (B.A.) Mathematics with Statistics Concentration and Computer Science, Bachelor of Arts (B.A.) Mathematics with Statistics Concentration and Computer Science at Swarthmore CollegeMath Concentration (2007 - 2011) English Concentration (2011 - 2014), Math Concentration (2007 - 2011) English Concentration (2011 - 2014) at Hanoi-Amsterdam High School for the Gifted
Vietnamese, English
Github Skills (23)
scipy10
spark10
probabilistic-programming10
python10
testing10
statistics10
machine-learning10
feature-engineering10
stat10
distributions10
statistic10
numpy10
scala10
automl10
jax10
Programming languages (5)
Github contributions (5)
salesforce/TransmogrifAI
Jul 2019 - Jul 2020
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 117 commits, 33 PRs in 1 year
Contributions summary:Tuan primarily contributed to the `transmogrifai` project by implementing and refining model insights, specifically focusing on feature importance and coefficient calculations for linear and logistic regression models. They addressed flakiness in the testing framework and incorporated moments and cardinality calculations for numeric and text features, enhancing the model analysis capabilities. Further contributions included enabling more loss types for `OpLinearRegression`, and fixing various test-related issues within the codebase.
pythonsalesforcetransformationstransmogrifyestimators
jax-ml/jax
Jul 2019 - Apr 2020
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Role in this project:Back-end Developer
Back-end DeveloperContributions:8 PRs, 49 comments in 9 months
Contributions summary:Tuan contributed significantly to the JAX library, primarily by implementing and extending statistical functions and numerical methods. They implemented Poisson distribution, flip functionality with axis=None, and the pinv function for linear algebra within the JAX ecosystem. Furthermore, the user added documentation for the `pinv` function and implemented the logistic distribution, demonstrating a strong focus on extending the mathematical capabilities of the library.
pytorchpythonjitautomatic-differentiationgpu
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