William Malpica
Principal Solutions Architect at NVIDIA
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolWilliam Malpica is a Principal Solutions Architect with nine years of software-focused experience and a decade-plus background in engineering leadership and productization. He co-founded and led engineering at GPU analytics startups (BlazingDB, Voltron Data), shipped a GPU-accelerated SQL engine and contributed C++ backend, memory and communication fixes to the high-profile RAPIDS ecosystem (BlazingSQL and cuDF), and now applies that deep data and systems expertise at NVIDIA. William combines hands-on backend and test automation skills with regulatory and product engineering experience from medical imaging—taking prototypes to FDA-cleared, production-ready systems. Comfortable moving between low-level performance tuning and organizational leadership, he’s known for turning research-grade code into maintainable, tested, scalable products. Based in Austin, he pairs an MS in electrical/biomedical engineering with a pragmatic focus on shipping reliable, high-performance data platforms.
9 years of coding experience
18 years of employment as a software developer
Electrical Engineering (MS) Biomedical Engineering and Image Processing, Electrical Engineering (MS) Biomedical Engineering and Image Processing at The University of Texas at Austin
English, Spanish
Github Skills (9)
unit-testing10
cudf10
c-language10
cprogramming-language10
test-automation10
sql9
parquet9
cuda9
parallel-computing8
Programming languages (7)
Github contributions (5)
BlazingDB/blazingsql
Sep 2018 - Sep 2021
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
Role in this project:
Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:18 releases, 194 reviews, 2087 commits in 3 years
Contributions summary:William's commits primarily involved modifications to C++ code within the engine directory, indicating back-end development focused on a GPU-accelerated SQL engine. The changes include code related to Parquet metadata handling, SQL expression parsing, and the structure of the data loaded. Additionally, the user worked on fixes and improvements related to memory management and communication between different nodes, which is crucial for database functionality.
blazingsqlcudfgpupythonrapids
NVIDIA/cudf
Jun 2018 - Feb 2020
cuDF - GPU DataFrame Library
Role in this project:Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:146 commits, 12 PRs, 148 comments in 1 year 8 months
Contributions summary:William primarily focused on improving the codebase by adding unit tests and cleaning up existing code, particularly concerning datetime operations. The user's work involved adding and validating unit tests for datetime operations with various data types in the cuDF library. This indicates a strong focus on ensuring the correctness and reliability of the library's functionality through comprehensive testing. In addition, the user contributed to enhancing the codebase by refactoring code, improving overall code quality, and fixing edge cases, leading to more maintainable and robust code.
cudfdataframegpurapidsarrow
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