📍 London, United Kingdom
💻 Software Engineer · Computer Graphics / ML Denoising R&D
I’m a software engineer with 15+ years of experience in animation, VFX, and feature-film production. I combine deep production experience with C++/CUDA and Python engineering, and a solid math background applied to ML denoising, image processing, and pipeline development.
- Denoise Machine X — Open-source modular C++ framework for CGI denoising with GPU-accelerated (CUDA) filters, temporal/spatial pipelines, multi-layer EXR support, and ML CNN (U-Net) denoising in progress.
- Ginzburg Denoiser — Standalone + Nuke plug-in denoiser used in production (Fixies series and feature), removing render noise up to 7x faster while preserving fine details, cutting render costs by 30%.
- JAM Asset Manager — A scalable Maya plug-in for asset/shot management, integrated into post-production pipelines to streamline publishing and improve collaboration.
Programming: C++, Python, Bash, MEL
ML / Deep Learning: PyTorch, TensorFlow, CNN/U-Net architectures, TensorBoard, NumPy, SciPy, Pandas, HDF5
Graphics & GPU: CUDA, OpenGL, DirectX, GLSL/HLSL, real-time rendering
Image Processing: OpenEXR, OpenCV, denoising algorithms, multi-layer EXR workflows
UI Development: Qt, PySide, PyQt
Pipeline / DCC: Maya, Houdini/Solaris, Katana, Nuke, Mari, 3ds Max, After Effects
Production APIs: Maya API, Nuke API, OpenUSD, ShotGrid
Renderers: RenderMan, Arnold, Redshift, Karma, V-Ray, Mental Ray
Real-Time: Unreal Engine
Backend / Web Services: FastAPI, REST APIs
Dev Practices: Git, CMake, GitHub Actions, CI/CD, GoogleTest, Docker
Platforms: Linux, Windows, macOS
📧 Email: ginzburgdd@gmail.com
🔗 LinkedIn
🎨 ArtStation
💻 GitHub