Timur Gadylshin
ML Team Lead at Yandex
Russia
Summary
🤩
Rockstar🎓
Top SchoolTimur Gadylshin is an ML Team Lead with a decade-long trajectory building and scaling applied AI systems, currently leading the ML Planner Pretrain team at Yandex to advance planning and decision-making for autonomous vehicles. He has progressed from C++ development and mathematical modeling in industry to senior research roles at Intel and PicsArt, then to leading video analysis and multimodal embedding efforts at VK where he delivered a universal multimodal content embedder, multi-tagging classifier, and content ID system. Timur blends hands-on research in model compression and neural networks with pragmatic productionization experience, particularly on multimodal and vision-language pipelines. Based in Russia and trained in applied mathematics, he is skilled at turning research insights into robust, deployable ML services that meet real-world product constraints. An understated strength is his cross-domain fluency—from low-level algorithmic optimization to product-facing model design—enabling teams to ship performant, scalable AI features.
5 years of coding experience
7 years of employment as a software developer
Специалист, Applied Mathematics, 4.88, Специалист, Applied Mathematics, 4.88 at Уфимский Государственный Авиационный Технический Университет
Английский
Github Skills (30)
transformers10
pytorch10
classification10
semantic-segmentation10
onnx10
openvino10
llm10
pruning10
deep-learning10
quantization-aware-training10
compression10
object-detection10
quantization10
nlp10
genai10
Programming languages (1)
Github contributions (3)
gadylshintr/nncf
Jan 2021 - Mar 2021
PyTorch*-based Neural Network Compression Framework for enhanced OpenVINO™ inference
Contributions:26 pushes, 9 branches in 1 month
pytorchneural-network-compressiondeep-learningcompressioninference
openvinotoolkit/nncf
Jan 2021 - Mar 2021
Neural Network Compression Framework for enhanced OpenVINO™ inference
Contributions:59 reviews, 5 commits, 5 PRs in 1 month
bertsemantic-segmentationmixed-precision-trainingtensorflowclassification
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