Benjamin Zaitlen
Senior System Software Manager at NVIDIA
Detroit Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolBenjamin Zaitlen is a senior system software leader with 14 years of experience building high-performance, distributed and GPU-accelerated systems at NVIDIA and Anaconda. He combines hands-on engineering—contributions to notable open-source projects like Dask, cuDF, cuML and CuPy—with team leadership driving system software, build automation, and reproducible data tooling. His background in physics and mathematics underpins a pragmatic approach to performance, memory management, and serialization issues across CPU/GPU stacks. Benjamin’s open-source work shows deep backend expertise (scheduler internals, dataframes, and build/release automation) and a knack for bridging developer ergonomics with production robustness. He also brings entrepreneurial and maker experience from founding a wearables electronics company, reflecting a persistent curiosity for applied hardware-software integration.
14 years of coding experience
17 years of employment as a software developer
Master of Science (MS) Physics, Master of Science (MS) Physics at Indiana University BloomingtonUniversity of California Santa Cruz
Stackoverflow
1,454reputation
81kreached
45answers
16questions
Github Skills (68)
postgresql10
python10
testing10
bash10
url-parsing10
distributed-computing10
automation10
gpu10
data-pipeline10
flask10
data-conversion10
bokeh10
scikit10
dataframes10
pandas10
Programming languages (19)
Github contributions (5)
dask/dask
Feb 2015 - Feb 2025
Parallel computing with task scheduling
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 reviews, 89 PRs, 63 pushes in 10 years 1 month
Contributions summary:Benjamin contributed primarily to the Dask dataframe library, focusing on enhancing its functionality and supporting new features. Their work included implementing features such as covariance and correlation calculations for grouped data, improving index handling, and supporting non-Pandas series within the unique method. Furthermore, they added resample methods to the dataframe and addressed various bug fixes related to testing.
pythonschedulingparallelnumpydask
rapidsai/cudf
Feb 2019 - Jan 2023
cuDF - GPU DataFrame Library
Role in this project:Back-end Developer
Back-end DeveloperContributions:58 reviews, 122 commits, 42 PRs in 3 years 11 months
Contributions summary:Benjamin focused on improving the `cudf` library, specifically addressing issues related to data frame creation and memory management. Their primary contributions involved modifying the code to ensure data continuity and contiguity when creating data frames from series, improving compatibility. They also added tests to validate the handling of non-contiguous NumPy arrays within the `cudf` framework. The user refactored code, moving contiguous checks and adding a top level merge function for convenience.
cudadataframe-librarydata-analysiscppcudf
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