James Liu
Senior User Experience Designer at Amazon
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJames Liu is a senior User Experience Designer based in Redmond with 16 years of cross-disciplinary experience designing 0-to-1 products and large-scale CX transformations at Amazon and AWS. He blends user-centered design, engineering fluency, and business impact—leading design systems and cross-team convergence that saved the organization engineering headcount and cut service costs by hundreds of millions. James has driven measurable outcomes across device setup, search tooling, and retail vendor onboarding, improving setup success, experimentation velocity, and conversion metrics. He pairs a fine arts and computer engineering background with hands-on development experience (including back-end contributions to the Treelite Java inference work), which gives him uncommon fluency between design intent and implementation. Colleagues rely on him to craft North Star visions, untangle complex journeys, and scale design systems that keep multiple stakeholders aligned.
16 years of coding experience
10 years of employment as a software developer
Bachelor of Fine Arts (B.F.A.), Minor in Commercial Design, Bachelor of Fine Arts (B.F.A.), Minor in Commercial Design at Chung Yuan Christian University
Chinese, English
Github Skills (8)
javas10
compilation10
java10
compile10
apidoc9
data-structure9
api9
data-structures9
Programming languages (3)
Github contributions (5)
dmlc/treelite
Apr 2018 - Jul 2018
Universal model exchange and serialization format for decision tree forests
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 16 PRs, 7 pushes in 2 months
Contributions summary:James focused on extending the Treelite project's Java compiler and inference engine. Their contributions include adding parameters for Java package and file prefix, enabling methods for setting and getting QValue in the Data interface, and refactoring the data and inference engine to use `ml.dmlc.treelite4j`. They also added an inference engine interface and made changes to use the Data interface instead of Entry.java in the prediction and refactored the inference engine.
decision-treeserialization
jamesliu/nanoPPO
Aug 2023 - Mar 2024
An efficient implementation of the Proximal Policy Optimization (PPO) algorithm with linear and attention policy for reinforcement learning.
Contributions:5 releases, 136 pushes, 2 branches in 7 months
proximal-policy-optimizationreinforcement-learning
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