Jamil Zakirov
Software Engineer at Picturino AI
Moscow, Moscow, Russian Federation
Summary
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RockstarJamil Zakirov is a software engineer based in Moscow with eight years of experience building ML-infused backend systems and computer vision tooling. He contributes to prominent open-source projects like Albumentations and piq, implementing image augmentations and rigorous image-quality metrics (including TV, FID and VIF) alongside comprehensive unit tests. Practical and hands-on, he blends engineering discipline—type hints, docs, bug fixes—with research-aware implementations that make academic metrics production-ready. An AI enthusiast who describes himself as a hustler, Jamil excels at turning experimental vision techniques into reliable library features used by the wider ML community.
8 years of coding experience
Github Skills (15)
unit-testing10
computer-vision10
pytorch10
machine-learning10
python10
numpy10
generative-adversarial-network9
opencv9
generative-model9
testing8
pytest8
scikit-image7
deep-learning6
deeplearning-ai6
data-augmentation6
Programming languages (6)
Github contributions (5)
photosynthesis-team/piq
Feb 2020 - Sep 2022
Measures and metrics for image2image tasks. PyTorch.
Role in this project:
Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:59 reviews, 65 commits, 84 PRs in 2 years 7 months
Contributions summary:Jamil's contributions focused on implementing and testing image quality assessment metrics within the "piq" library. They added the "total_variation" (TV) metric, including the core code and comprehensive unit tests for functionality verification. Moreover, the user contributed to the implementation and testing of "Frechet Inception Distance" (FID) and other image quality metrics, such as the Visual Information Fidelity (VIF) metric. This work included the addition of both code and unit tests, indicating a focus on both model implementation and validation.
vifbrisquemsepsnrimage-quality
albumentations-team/albumentations
Nov 2021 - Jun 2022
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Role in this project:ML Engineer
ML EngineerContributions:6 reviews, 5 commits, 6 PRs in 7 months
Contributions summary:Jamil primarily contributed to the implementation of image augmentation techniques within the Albumentations library. Their work included the creation of new image transformations like `UnsharpMask`, `RingingOvershoot`, and `AdvancedBlur`, alongside the addition of unit tests and the integration of these transforms into the library's functionality. Furthermore, the user addressed bug fixes, type hinting, and documentation improvements related to the newly added transforms.
fast-augmentationspythonalbumentationsdetectiondeep-learning
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