Radoslaw is a Senior Python Developer with 15+ years of experience crafting high-level software solutions using fundamental design principles and best practices to develop server-side logic, high-performing services, and new features. He is an expert in web programming, Machine Learning, image recognition, and data analysis. Radoslaw excels in collaborating effectively on teams, discussing innovative ideas, integrating new technologies, and testing new approaches.
Worked on distributed and scalable solutions for clients and created robust Python components.
Architected technical requirements and deployed resources to deliver robust, maintainable solutions.
Participated in technical architecture discussions and peer code reviews, recommending ways to improve code quality and push for reliability across different stacks.
Implemented measurable technical standards to ensure the long-term success of projects.
Built tools and processes and architected new features and solutions.
Created contextual widgets for skysports.com with a built-in CMS solution for developers to configure complex rules about priority of competitions and team players.
Repaired the structure of the gambling API used by Sportsbook using Tornado/Redis to process about 1,000 requests per second.
Implemented core features for online casinos including payment transactions and account management integration with the NYX platform.
Improved Transporeon's code coverage for an internal application from 20% to 85%, rewriting most of the legacy code with no rollbacks needed for 2 years.
Created a GUI test framework to help testers in their daily routines.
Implemented new features with pricing models for complex options, statistic module, and integration with external APIs.
The team's primary objective was to develop advanced algorithms for human decision support in criminal activities involving dangerous objects.
They created prototypes to enhance the accuracy of recognizing dangerous tools from CCTV monitoring.
The team developed real-time vision systems for detecting and recognizing dangerous tools, including weapons, using Neural Networks and PCA transformations.
