Product Search and Logistics Automation

• Developed a search robot for products, increasing cold client conversions by 4%.
• Created a report monitoring system for item positions for clients.
• Developed an advanced route-planning algorithm for courier logistics, increasing daily pickup points by 13%.
• Added generation of invoices for product stock, improving product acceptance process speed and accuracy by 15%.

Led a team of 3 developers in designing and maintaining RuBackup’s software ecosystem.

Designed and implemented a modular Python library for backup integrations, now published on PyPi.

Released the first stable version of the web interface and REST API for RuBackup’s backup control system.

Developed and deployed an autoregressive model using statsmodels to predict remaining storage capacity.

Formalised internal coding standards, GitLab practices, and documentation processes to improve code quality and maintainability.

• Trained a computer vision model to detect vehicle scratches and damage from images.

• Built a containerised service using Docker for model deployment.

• Enhanced image preprocessing pipeline to boost model accuracy and generalisation.

• Improved UX and performance of an industrial PLM system using Next.js and NiFi.
• Refactored legacy Vue.js project to enhance business process security.
• Built a custom SQL database to support logistics for industrial materials.

• Trained and deployed face detection and feature extraction models to production.

• Created APIs and inference pipelines using Triton Inference Server and TensorRT.

• Designed a video stream processing system handling input from multiple cameras.

• Increased vector search performance 20x by optimising FAISS-based similarity search.

• Built dockerised infrastructure for scalable deployment.