Seung Lee
Software Engineer at Bloomberg LP
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolSeung Lee is a Software Engineer at Bloomberg in New York with 11 years of experience applying machine learning and engineering to real-world data problems. He builds systems that extract structured information from unstructured text using large language models and has practical experience compressing and accelerating embedding models for production financial data. His open-source contributions span ML and tooling—improving usability in Optuna, adding NLP transformations in NL-Augmenter, and updating TF-Agents examples—reflecting both applied ML and attention to developer experience. Previously he prototyped exploration algorithms for TensorFlow, ranked in a Microsoft Research dialog challenge, and co-founded a startup, demonstrating a mix of research, product, and hands-on engineering.
11 years of coding experience
2 years of employment as a software developer
Bachelor’s Degree, Mathematics, Bachelor’s Degree, Mathematics at Princeton University
Korean, English
Stackoverflow
65reputation
3kreached
0answers
4questions
Github Skills (27)
algorithm10
algorithms10
ppp10
python10
command-line-interface10
sac10
reinforcement-learning10
dqn10
tensorflow10
command-line10
nlp10
cli10
json9
nltk9
hyperparameter-optimization9
Programming languages (10)
Github contributions (5)
tensorflow/agents
Apr 2019 - Oct 2019
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Role in this project:
ML Engineer
ML EngineerContributions:15 commits, 10 PRs, 19 comments in 6 months
Contributions summary:Seung primarily updated example scripts within the TF-Agents library, focusing on various reinforcement learning algorithms such as DQN, PPO, and SAC. These updates included modifying command-line arguments, correcting typos in documentation, and standardizing directory structures for running the examples. The user's changes involved multiple example scripts, demonstrating a broad understanding of the library's agent implementations.
scalabletf-agentsmultiagent-reinforcement-learningtensorflow-librarymulti-armed-bandits
GEM-benchmark/NL-Augmenter
Jul 2021 - Sep 2021
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:ML Engineer
ML EngineerContributions:4 reviews, 11 commits, 1 PR in 2 months
Contributions summary:Seung contributed to the `nl-augmenter` repository by implementing a color transformation. They added a Python script to the `transformations/color_transformation` directory to replace color names in a sentence with other color names. Further commits refactored the transformation to use a JSON file for color names and introduced custom mapping functionality. The final commit added keywords to the transformations.
nlpinformation-theorysentencedeep-learningmachine-learning
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