Keon Kim
Co-Founder at Angel Investing
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKeon Kim is a San Francisco–based co-founder and software engineer with 11 years of experience building backend systems and production ML tooling. He previously led backend work at Uber on driver pricing and incentive products, and now builds AI agents at Om Labs after selling wallet infrastructure IP to Silence Labs. Keon combines practical ML expertise—demonstrated by open-source implementations of DQN/DDQN, seq2seq with attention, and reinforcement-learning examples—with robust backend skills in C++ and Python. He’s an active contributor to mlpack and clean educational repos that reflect a focus on reproducible, minimal implementations for learning and production. An angel investor in ambitious deep-tech and space startups, he brings a founder’s perspective to product and engineering trade-offs. Collectedly, his profile blends hands‑on ML engineering, systems design, and early-stage investing insight.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Arts (BA) Computer Science, Bachelor of Arts (BA) Computer Science at New York University
Stackoverflow
750reputation
115kreached
7answers
36questions
Github Skills (51)
algorithms10
pytorch10
machine-translation10
c-language10
python10
encoder10
attention-mechanism10
command-line-interface10
machine-learning10
decode10
seq2seq10
data-structure10
reinforcement-learning10
keras10
dqn10
Programming languages (14)
Github contributions (5)
rlcode/reinforcement-learning
Jan 2017 - Jul 2017
Minimal and Clean Reinforcement Learning Examples
Role in this project:
ML Engineer
ML EngineerContributions:59 commits, 39 PRs, 57 pushes in 5 months
Contributions summary:Keon primarily contributed to reinforcement learning examples, focusing on implementing and updating deep Q-network (DQN) algorithms for the CartPole environment. They modified existing code related to DQN, Keras, and the CartPole environment, and also created/updated files for the Keras CartPole DQN, REINFORCE, and other related files. The contributions demonstrate the user's focus on practical applications of reinforcement learning techniques.
reinforcement-learningdeep-learningdeep-reinforcement-learningmachine-learningpolicy-gradient
keon/algorithms
Nov 2016 - Dec 2019
Minimal examples of data structures and algorithms in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 release, 1 review, 114 commits in 3 years 1 month
Contributions summary:Keon primarily contributed to the implementation of various algorithms and data structures in Python, as evidenced by the code modifications across multiple files. The commits involve the creation and modification of sorting algorithms, linked lists, tree traversals, search algorithms, and dynamic programming solutions. Furthermore, the user added solutions for string manipulation and graph traversals. The focus is on providing concise Python implementations of fundamental computer science concepts.
data-structuredata-structurespythoncompetitive-programmingsort
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