Eliyar Eziz
Head Of Engineering at Yodo1 Games
Chaoyang District, Beijing, China
Summary
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Rockstar🎓
Top SchoolEliyar Eziz is a Head of Engineering with 11 years of experience leading cross-functional teams and shipping production ML systems from Beijing’s Chaoyang District. He blends hands-on expertise in NLP and Python—recognized as a Google Developer Expert in ML—with strategic leadership at Yodo1 Games. Earlier roles include building NLP task bots from scratch at Baofeng, demonstrating end-to-end ownership of research-to-production pipelines. As a core contributor to Kashgari, he implemented tokenization, embeddings (Word2Vec, BERT, GPT-2) and sequence-labeling models, showing a strong open-source pedigree in production-ready NLP tooling. He also has practical mobile experience, having developed and refactored an iOS video player supporting multi-quality playback and subtitles. Author of a TensorFlow 2 book, Eliyar pairs technical authorship with product-focused engineering leadership.
11 years of coding experience
4 years of employment as a software developer
学士, 光信息科学与技术, 学士, 光信息科学与技术 at 合肥工业大学
English, Chinese, uyghur
Stackoverflow
334reputation
8kreached
10answers
0questions
Github Skills (22)
word2vec10
python10
sequence-labeling10
machine-learning10
text-classification10
keras10
deep-learning10
tensorflow10
avplayer10
swift10
nlp10
ui-design9
embedding9
initialization6
avaudioplayer6
Programming languages (15)
Github contributions (5)
BrikerMan/BMPlayer
Apr 2016 - Jul 2020
A video player for iOS, based on AVPlayer, support the horizontal, vertical screen. support adjust volume, brightness and seek by slide, support subtitles.
Role in this project:
Mobile Developer (iOS)
Mobile Developer (iOS)Contributions:9 releases, 2 reviews, 239 commits in 4 years 2 months
Contributions summary:Eliyar's commits focus on developing an iOS video player application. The primary focus is on implementing features related to video playback, including adding a video list view, playback time display, and adding subtitles. The commits also touch on UI improvements and gesture controls, showcasing the user's work within the iOS mobile development domain. The user is also responsible for refactoring the video player to support multiple video qualities.
swift5video-playeriosvideoplayer
BrikerMan/Kashgari
Jan 2019 - Jul 2021
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:29 releases, 4 reviews, 913 commits in 2 years 6 months
Contributions summary:Eliyar primarily focused on developing the core functionality for text classification and sequence labeling within the Kashgari NLP framework. Their contributions included implementing tokenization, word embedding techniques such as Word2Vec, and models for text classification and NER using deep learning. Key changes involved preparing base structures, adding pre-processing tools, and refining the training process for the implemented models.
bertword2vecframework-learningon-toptf-keras
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