Artem Romanov specializes in commercial development, primarily working with Kotlin and Java for mobile applications, and is also involved in machine learning. His experience combines fundamental approaches, such as REST and the creation of high-load systems, with more niche areas, including custom training of neural networks. In addition to programming, Artem also has an engineering background.

Reviews

Artem Romanov is a highly qualified specialist with a deep understanding of technical challenges, particularly in the area of Linux architecture and automation. Reviews confirm his promptness, precise execution of technical specifications, professional communication, and ability to tackle complex tasks comprehensively. Many clients describe him as a responsible, knowledgeable, and client-oriented performer, often exceeding expectations. No negative feedback has been reported.

Portfolio projects

Skills and Technologies: Go, Swift, Python, REST API, SQLite, PostgreSQL, HTTP, Docker, Bash, JSON, CSV, web development, mobile development, interface design.

Projects and Achievements: The candidate has developed several projects, including a demo integration of an iOS client with a Go backend for working with a closed API, as well as a service for a desktop application featuring a local admin panel and network request queues. As part of traffic analysis and diagnostics of changes in the external API, a tool for parsing HTTP sessions was created. The candidate also worked on data migration from MSSQL to PostgreSQL, developed Android applications for couriers and training, and conducted a research project to test strategies in the cryptocurrency market. The results of these projects include the creation of adaptive interfaces, simplification of migration processes, and automation of data handling.

Achievements and Recognition: The candidate successfully implemented projects that led to significant improvements in API workflows and reduced risks during data migration. His portfolio showcases tools that assist in diagnostics and analysis, as well as applications with intuitive interfaces tailored for users.

* It is created by a neural network based on a portfolio, information provided by the user about himself and reviews from other users.

русская версия