Position: Computer Vision Engineer | Machine Learning Engineer
Category: Data Science
English level: intermediate
Years of experience: 5

Kaggle bengaliai-cv19 (Top 6% bronze winner)
Computer Vision Engineer
- Investigate and train deep learning models to develop computer vision algorithms for Manufacturing Industry (Object detection, Anomaly detection, Segmentation)
- Built a pipeline and trained license plate recognition system. Achieved accuracy of 99.2% (С++, Python, TensorRT) for Jetson
- Developed synthetic data generation algorithm for license plates based on GANs. The generated data improved the accuracy of the license plate recognition system by 2% by dealing with imbalanced data
- Researched quantization techniques for deep learning model compression. Managed to quantize the FaceNet model to work on Google Coral
- Working with stable diffusion models(lora, dreambooth) for img2img translating
- Developing vehicle/person re-identification from multiple camera for smart city analytics
- Developed a system that analyzed HTTP requests with regular expressions to prevent malicious behavior. Prevented 95% of the most common HTTP attacks
- Redesigned the app’s architecture from monolith codebase to microservices using Golang, ClickHouse, Postgresql, gRPC. It improved uptime, performance, and scalability
- Designed and developed a Face Recognition system using Angular 6, Django, MXNET, and Postgresql.
I am interested in Computer Vision, and NLP field projects.