Python Team Lead, IoT Solutions (вакансія неактивна)

4+ years of experience working with Python
Experience and desire to lead development in medium to large distributed teams
Knowledge of Django, Flask and Celery.
Experience in creating client-server applications and RESTful services
Good spoken English

Experience with JavaScript
Experience working with AI technologies
Experience working in the IoT industry

Professional Development:
— Experienced colleagues who are ready to share knowledge;
— The ability to switch projects, try yourself in different roles;
— Over 150 internal courses for advanced workplace-based training;
— Study and practice of English: courses and communication with colleagues and clients from different countries;
— Support of speakers who make presentations at conferences and meetings of technology communities.
The ability to focus on your work: a lack of bureaucracy and micromanagement, and convenient corporate services;
Lack of dress code, friendly atmosphere, concern for the comfort of specialists;
Flexible schedule and the ability to work remotely;
The ability to work in any of our development centers.

DataArt’s client develops AI solutions in the area of automated bridge inspections. This innovative solution includes taking photos of bridges using IoT solutions, processing the frames using AI, and transferring them to the UI.

DataArt’s specialists are helping with developing the platform. The next step will be creating a marketplace and adding new features. DataArt’s team consists of 8 people (2 backend and frontend developers, a DevOps specialist, a solutions architect, a designer, and a project manager).

The specialist will have to take on the tasks of leading a team, which is currently being led by an engineering manager on the client side. The Python specialist will work directly with the solutions architect and a project manager from DataArt to help organize the work. A business trip to the client’s office in Austria is planned to get you acquainted with the project partners.

The system’s backend is being implemented with Django + Flask + Celery. The Frontend us using JavaScript, Vue.js, Nuxt.js, Material Design, and JS Beautify.