Bernardt Duvenhage

Alberta, Canada

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Summary

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Senior

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Top School

Bernardt Duvenhage is a Machine Learning Mission Specialist and Staff Engineer with 15 years of experience building production-grade AI systems, from embedded vision and robotics to large-scale video generation and editing. He co-founded and served as CTO of Pipio, where he built the initial deep learning models and rendering backend for AI-generated talking-head videos and led the company through due diligence and team growth. At VEED and Toptal he now focuses on foundational models and novel techniques for video synthesis, while earlier roles at Feersum Engine and Helm drove machine comprehension, dialogue agents and multilingual NLP for real-world services. He brings deep systems expertise in C++, Python, CUDA and PyTorch, and has productionized algorithms across GPU-accelerated pipelines, realtime image-processing frameworks and low-power platforms. An active open-source contributor, he improved NumPy’s random number generators with a high-performance implementation of Lemire’s algorithm and cross-platform fixes. He holds a PhD in Computer Science (computer graphics) and blends academic rigor with hands-on engineering and startup leadership.

15 years of coding experience

19 years of employment as a software developer

PhD in Computer Science Computer Graphics (Supervised by Prof DG Kourie and Prof K Bouatouch), PhD in Computer Science Computer Graphics (Supervised by Prof DG Kourie and Prof K Bouatouch) at University of Pretoria

English, Afrikaans

Github Skills (11)

c1710

algorithm10

randomization10

data-structures10

algorithms10

c1110

performance-optimization10

python10

data-structure10

numpy10

unit-testing9

Programming languages (5)

C++CJupyter NotebookElixirPython

Github contributions (5)

numpy/numpy

Oct 2018 - Jun 2019

The fundamental package for scientific computing with Python.

Role in this project:

Back-end Developer / Data Scientist

Contributions:5 commits, 3 PRs, 30 comments in 8 months

Contributions summary:Bernardt primarily contributed to the implementation and optimization of random number generation algorithms within the NumPy library. Their work involved adding Lemire's algorithm as an alternative method for generating random numbers in an interval, improving performance. This included modifications to the `distributions.c` file and updates to the `generator.pyx` file, along with the addition of unit tests to validate the new functionality. They also corrected compilation errors on Visual Studio and improved the code's maintainability.

lapackpythonmpindarrayconvolution

praekelt/feersum-lid-shared-task

Oct 2017 - Nov 2019

Contributions:29 commits, 24 pushes, 1 branch in 2 years 2 months

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