Wansoo Kim
Software Engineer at Rebellions
Seoul, South Korea
Summary
🤩
RockstarWansoo Kim is a software engineer based in Seoul with 8 years of experience specializing in Kubernetes, container ecosystems, and optimizing resource efficiency for both public cloud and on-prem GPU/NPU AI infrastructure. He has progressed from backend and ML engineering roles into platform leadership, most recently serving as Platform Engineering Team Lead at Riiid and now driving infrastructure work at Rebellions. A pragmatic open-source contributor, Wansoo has improved core projects like NumPy, TensorFlow Addons, and dm-haiku—optimizing numerical correctness and refactoring hotspots to boost maintainability and performance. His hands-on work spans deep RL implementations and privacy-preserving ML tooling (PySyft), reflecting a blend of low-level numerical care and production-grade platform thinking. Colleagues know him for squeezing efficiency from compute stacks and for a developer-first approach to scalable AI infrastructure.
8 years of coding experience
5 years of employment as a software developer
Github Skills (32)
algorithm10
code-optimization10
algorithms10
pytorch10
ppp10
python10
machine-learning10
reinforcement-learning10
refactor10
numpy10
deeplearning-ai10
deep-learning10
tensorflow10
optimisation10
federated-learning10
Programming languages (13)
Github contributions (5)
archsyscall/DeepRL-TensorFlow2
Mar 2020 - May 2020
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Role in this project:
ML Engineer
ML EngineerContributions:95 commits, 1 PR, 86 pushes in 1 month
Contributions summary:Wansoo implemented various Deep Reinforcement Learning (DRL) algorithms within the repository, specifically focusing on Actor-Critic methods like A2C and A3C, and PPO. Their work involved defining actor and critic networks, developing action selection and loss functions, and integrating these components into an agent framework. The user's commits demonstrate a focus on building and refining the core DRL components, including model architectures and training procedures.
deep-reinforcement-learningtensorflowmachine-learningreinforcement-learninga2c
hyperopt/hyperopt
Apr 2020 - Aug 2021
Distributed Asynchronous Hyperparameter Optimization in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:14 reviews, 55 commits, 39 PRs in 1 year 4 months
Contributions summary:Wansoo primarily focused on refactoring and optimizing the codebase of the hyperparameter optimization library. Their commits involved replacing if/else statements with ternary operators and early returns, as well as other code reduction strategies. They also addressed performance issues by eliminating unnecessary repetitive operations. This work improved the readability and efficiency of the code.
asynchronoushyperparameter-optimizationpython
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