Miles Macklin
Summary
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RockstarMiles Macklin is a Senior Director of Engineering at NVIDIA with 13 years of experience building and optimizing GPU-accelerated simulation and graphics systems. He has progressed from senior graphics roles in games to leading NVIDIA’s simulation technology roadmap, including contributions to Warp—a high-performance Python framework for GPU simulation—and earlier work on Flex and PhysX. Miles blends deep research (PhD-level) expertise in physics simulation and numerical methods with hands-on performance engineering in CUDA and C++, shipping production-ready tools for robotics, CAE/CFD, and physical AI. He is known for refactoring core simulation stacks for cross-platform reliability and for pragmatic innovations in collision, constraint solving, and time integration that enable real-time training and inference. Colleagues rely on him to translate advanced algorithms into scalable developer-facing platforms that external partners can adopt. An underappreciated strength is his background in console graphics optimization, which informs his relentless focus on performance at both low-level kernels and whole-system design.
13 years of coding experience
Github Skills (8)
cuda10
gpu-programming10
performance-optimization10
python10
code-generation9
c-language8
numerical-methods8
cprogramming-language8
Programming languages (3)
Github contributions (5)
NVIDIA/warp
Mar 2021 - Oct 2022
A Python framework for GPU-accelerated simulation, robotics, and machine learning.
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:10 releases, 2 reviews, 75 commits in 1 year 7 months
Contributions summary:Miles focused on developing and optimizing the `warp` framework, specifically targeting high-performance GPU simulation and graphics. Their contributions involved fixing module cache checks, implementing support for macOS and Linux platforms, and refactoring core components such as types, context, and code generation to improve integer handling. The user also made significant progress on the wave equation test and the CUDA backend.
gpumachine-learningpythonroboticssimulation
mmacklin/tinsel
Sep 2016 - Jun 2020
Lightweight CPU/GPU path tracer
Contributions:75 commits, 6 pushes, 1 branch in 3 years 9 months
gpu
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