Nijat Zeynalov
AI Solutions Team Lead at Proxima Tech Solutions
Baku City, Azerbaijan
Summary
👤
Senior🎓
Top SchoolNijat Zeynalov is an AI Solutions Team Lead with 8 years of engineering experience and 3+ years focused on building and deploying machine learning systems across NLP, computer vision, and predictive modeling. AWS ML certified and a Google TensorFlow Developer, he has led teams and product development while delivering production-grade MLOps pipelines and model-serving solutions for telecom and enterprise clients. His work includes inventive applications—positive-unlabeled learning for customer targeting, OCR via homography, and face liveness detection—paired with hands-on deployment on AWS. A former founder who trained 200+ students and a Visiting Researcher at the University of Cambridge, Nijat blends technical depth with product and educational leadership. Based in Baku, he combines practical engineering, cloud-native MLOps, and a knack for turning experimental ideas into reliable production features.
8 years of coding experience
6 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Azerbaijan State Oil and Industry University • ASOIUMaster of Business Administration - MBA, Master of Business Administration - MBA at Ukranian State Biotechnological UniversityBachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at SABAH groupsMaster of Science - MS Innovation and Technology Management, Master of Science - MS Innovation and Technology Management at University of Tartu
Github Skills (44)
content-based-recommendation9
machine-learning7
aws-ecs7
mnist-dataset7
automl6
kitchen6
use-case6
docker-image6
neural-network5
telegram-bot5
retail5
fastapi5
time-series4
mnist4
cosine-similarity4
Programming languages (2)
Github contributions (5)
NijatZeynalov/NijatZeynalov
Jul 2020 - Jan 2025
Contributions:3 pushes, 1 branch in 4 years 7 months
NijatZeynalov/New-product-demand-forecasting-via-Content-based-learning-for-multi-branch-stores
Dec 2022 - Dec 2022
New product demand forecasting via Content based learning for multi-branch stores: Ali and Nino Use Case
Contributions:27 commits, 4 PRs, 5 pushes in 1 day
forecastingdocker-imagedartsuse-casetime-series
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