Charlie Wang - Senior Research Scientist at NVIDIA

Charlie Wang

Senior Research Scientist at NVIDIA

Mountain View, California, United States

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Summary

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Rockstar

🎓

Top School

Charlie Wang is a senior research scientist in Mountain View with 12 years of experience building and evaluating large language models, agentic systems, and practical ML infrastructure. He blends deep academic training (PhD work in Bayesian optimization at Cornell) with hands-on engineering—from GPU-accelerated modules at Yelp to leading LLM research and product efforts across startups and labs. Charlie has driven post-training and evaluation research at NVIDIA and led LLM teams at WIZ.AI and BAAI, demonstrating an ability to move models from research into production. His background includes co-founding a Beijing AI startup and contributing backend improvements to notable open-source tooling like Yelp’s MOE, where his CUDA and refactoring work improved performance and maintainability. Comfortable at the intersection of research and engineering, he focuses on measurable metric optimization and scalable model evaluation pipelines. Colleagues rely on him for rigorous experimentation, production-focused research, and pragmatic system-level solutions.

12 years of coding experience

7 years of employment as a software developer

Bachelor of Science (BSc), Physics, Bachelor of Science (BSc), Physics at Nanyang Technological University

PhD, Operations Research & Information Engineering, PhD, Operations Research & Information Engineering at Cornell University

University of Illinois Urbana-Champaign

Github Skills (6)

string-formatting10

string-format10

python10

documentation7

cprogramming-language5

c-language5

Programming languages (2)

C++Python

Github contributions (5)

Yelp/MOE

Jun 2014 - Apr 2016

A global, black box optimization engine for real world metric optimization.

Role in this project:

Back-end Developer

Contributions:111 commits, 1 PR, 2 pushes in 1 year 11 months

Contributions summary:Charlie primarily focused on refactoring code related to string formatting within the project's codebase, replacing older string formatting methods with the newer 'format' method. This involved modifications across multiple files, including data containers, setup scripts, and example files. Furthermore, the user contributed to the documentation files, particularly the cpp_rst_maker.py file.

boxoptimizationblack-box-optimizationblack-boxespn

jialeiwang/jialeiwang.github.io

Jun 2017 - Dec 2017

Contributions:40 pushes, 1 branch in 6 months

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