Position: Full Stack Web Developer
Category: Node.js
English level: fluent
Years of experience: 3


- Architected, developed and deployed real-time proctoring system for Kazakh Unified National Test (ЕНТ) designed for up to 6’000 concurrent users using Machine Learning based violation detection.
- System incorporated node.js, react, postgres, redis, PyTorch, TorchServe technologies and was deployed on with help of docker, k8s, AWS, Yandex.Cloud
- Curated data gathering and learning process for Computer Vision models, such as YoloV3, FasterRCNN, ResNet
- Developed Web frontend CMS using React, Antd, cross-platform mobile client using React-Native and backend using experss.js, all in Typescript.
- Improved Alice’s skill recommendation system by augmenting training data sets and training various new CatBoost models.
- Successfully developed realtime Image Recognition App using python, customized version of YOLO neural network and OpenCV together with Nvidia Jetson, Arduino Controller and Raspberry PI’s camera on hardware side.
- Assisted on training and validation of customized crop-weed image recognition neural network based on YOLO model