Position: Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 0.5

Winner of hackathon HackNU 2023 (2nd place, 400+ teams)
Winner of RBK Bank Hackathon 2022 (2nd place)
Winner of SDU Proficiency Test Olympiad
International Conference on Electronics Computer and Computation (ICECCO) 2023 Speaker
ICECCO 2021 Speaker
Author of Telegram channel 'IT Community of SDU' (2600+ subscribers, 2000+ views per post, collaborations with JetBrains, Beeline, Kolesa, and others.)
• Trained classification and segmentation model for MRI images and markups using PyTorch Lightning.
Performed hyperparameter tuning with Optuna. The dice score was 87%. Posted article on Medium.
• Implemented a service for processing MRI pictures and sending coordinates of segmented areas with OpenCV.
The service assisted the doctors to segment and detect the deceased areas of the brain.
• Trained classification and segmentation model of hemorrhagic stroke blood type for CT images using 2.5D
technique. It helped to decrease the weight of the model on the server and still classify and segment blood as
well as with 3D images.
• Made a live dashboard with Streamlit. Used Apache Airflow for DAGs management. The dashboard helped
to track the statistics of diagnoses by each week. Used pandas, matplotlib, seaborn, pylab. for EDA.
I want to find a position as Junior Machine Learning Engineer, where I could learn from my colleagues (mentors).