Dmitry Shabat is a computer vision and ML engineer with 8 years of hands-on experience turning state-of-the-art research into production-grade 3D reconstruction and perception systems. As a founding team member at Medida AI and earlier roles at Gracia AI and Clostra, he built and optimized NeRF-based pipelines, accelerated inference on edge devices, and scaled dynamic neural scenes by an order of magnitude. He combines CUDA performance tuning, MLOps automation, and pragmatic data-pipeline engineering to consistently boost training and inference throughput while improving scene quality from imperfect inputs. Dmitry’s work spans full-stack ML delivery—from rapid MVPs integrating LLMs and detection models to clinical-grade imaging models that doubled expert review speed. Based in Tel Aviv with a background in mathematics and computer science, he’s comfortable both reproducing bleeding-edge papers and shipping products that “just work.” A lesser-known strength is his knack for squeezing practical gains from messy real-world data, turning research prototypes into reliable deployments.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Mathematics and Computer Science, Bachelor's degree, Mathematics and Computer Science at Higher School of Economics
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