Christopher Crouzet
Senior Software Engineer at NVIDIA
Wellington, Wellington, New Zealand
Summary
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Rockstar🎓
Top SchoolChristopher Crouzet is a senior software engineer with 12 years’ experience transitioning from a technical artist in VFX to building high-performance developer tools and GPU compute kernels. Currently contributing to NVIDIA Warp, he has improved core numerical routines and dynamic module support for a widely used GPU simulation framework, combining practical pipeline design with low-level optimization. His background delivering resilient tools for hundreds of artists at Weta Digital and Unity gives him a strong product-minded focus on user experience, maintainability, and reducing technical debt. Self-taught and relentlessly curious, he thrives on challenging problems around rendering, simulation and real-time systems and quickly masters unfamiliar domains. Based in Wellington, he pairs creative problem framing from film production with rigorous software architecture to drive impactful engineering outcomes.
13 years of coding experience
3 years of employment as a software developer
Baccalauréat S, Sciences, Baccalauréat S, Sciences at Lycée Honoré Daumier, Marseille, France
French, English, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
cuda10
gpu-programming10
c-language10
cprogramming-language10
python10
architecture9
architectures9
numerical-methods9
Programming languages (8)
Github contributions (5)
NVIDIA/warp
Oct 2022 - Jan 2023
A Python framework for GPU-accelerated simulation, robotics, and machine learning.
Role in this project:
Backend Developer & Software Architect
Backend Developer & Software ArchitectContributions:4 reviews, 39 commits, 2 PRs in 3 months
Contributions summary:Christopher significantly contributed to the `warp` project by introducing support for transient modules, which enhances dynamic module creation and management within the framework. They refactored the `lerp` function by computing `adj_lerp()` using `tensordot()`, demonstrating an understanding of numerical methods and optimization. Additionally, the user implemented a new `smoothstep` built-in function and improved the handling of spatial matrix multiplication and device selection, indicating their focus on improving the core functionalities of the project.
gpumachine-learningpythonroboticssimulation
christophercrouzet/eddi
Oct 2017 - Jun 2018
Contributions:2 releases, 28 commits, 15 pushes in 8 months
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