Vladimir C.

About

Volodymyr is a seasoned Deep Learning & Computer Vision Engineer with deep expertise in Generative AI and media synthesis. In recent years, he has specialized in architecting complex systems from the ground up-ranging from developing Image-to-Video and Lipsync modules to deploying scalable services powered by Stable Diffusion. His background covers the entire ML product lifecycle, from initial R&D and model training in PyTorch to deep inference optimization using TensorRT and ONNX for real-time applications. Throughout his career, Volodymyr has successfully delivered high-impact, technologically sophisticated projects, including AI-driven content creation platforms, 3D head reconstruction systems, and real-time analytical solutions for sports broadcasting and fitness. He is highly proficient with the Diffusers library and has extensive experience with Image-to-Mesh pipelines and complex multi-object tracking. Beyond model development, he places a strong emphasis on infrastructure and MLOps (Docker, ClearML, DVC), ensuring the stability and reproducibility of experiments in production environments. His primary focus is striking the perfect balance between high-fidelity generation and system performance. Volodymyr excels at optimizing GPU memory consumption and accelerating neural networks, enabling the deployment of heavy models under high-load conditions or on edge devices without compromising quality.

Key Expertise