Antoni Baum
Member Of Technical Staff at Anthropic
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAntoni Baum is a Member of Technical Staff at OpenAI with 11 years of experience building distributed systems, LLM/GenAI infrastructure, and pragmatic 0-to-1 products. He combines deep systems and ML engineering chops—contributing to high-profile open-source projects like Ray, vLLM, Hugging Face Transformers, and PyCaret—with hands-on performance and deployment work that spans placement groups, distributed training, and inference optimizations. Previously at Anyscale he focused on production-grade LLM systems and hyperparameter tuning for time-series and optimization tasks. Antoni’s contributions often sit at the intersection of backend engineering and ML tooling—adding new parameter types, robust sampling methods, and cross-framework fixes that improve real-world distributed workflows. Based in San Francisco, he pairs a rigorous MSc in Computer Science & Econometrics with a bias for execution, delivering comprehensive solutions under practical constraints.
11 years of coding experience
5 years of employment as a software developer
Master (MSc.) Computer Science & Econometrics, Master (MSc.) Computer Science & Econometrics at AGH University of Krakow
English, Polish
Github Skills (29)
pytorch10
distributed-training10
python10
data-science10
scikit10
machine-learning10
inference10
llm10
hyperparameter-optimization10
bayesian10
deep-learning10
optimisation10
natural-language-processing10
scikit-learn10
data-handling10
Programming languages (17)
Github contributions (5)
pycaret/pycaret
Aug 2020 - Jan 2023
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:19 releases, 491 reviews, 1526 commits in 2 years 5 months
Contributions summary:Antoni's contributions primarily revolved around enhancing the functionality of the `pycaret/pycaret` library, a low-code machine learning project. Their work included tweaking and improving existing code within the internal plot modules responsible for residual plots, as well as enhancing the `tabular.py` module to address best parameter retrieval for tunable models. Furthermore, the user's commits demonstrate a focus on improving code related to iterative imputation and model interpretation, suggesting a focus on data analysis and model development, within the specified scope of the project.
automllow-codepycaretpythonreact
ray-project/ray
Aug 2020 - Jan 2023
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:1238 reviews, 270 commits, 361 PRs in 2 years 5 months
Contributions summary:Antoni contributed to the Ray Tune library, adding support for various sampling methods. The contributions focused on enhancing the search space and providing tools for tuning hyperparameters, specifically in the context of time-series models and optimization tasks. The user implemented features such as integer loguniform support and a more robust approach to handling numerical values. The contributions involved the core library of ray tune, with changes affecting various key files in the repository.
aimachine-learningraydistributedparallel
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