User Interface (UI) Developer - Qt / Python / MATLAB / LabVIEW

User Interface (UI) Developer - Qt / Python / MATLAB / LabVIEW

Job Summary :

We are looking for creative and technically-oriented UI developers to assist in designing, developing, and testing interactive graphical user interfaces (GUI) and visualization tools for embedded and scientific applications. The ideal candidate will possess basic proficiency in Qt framework and Python programming, with familiarity or interest in MATLAB and LabVIEW environments. This role involves hands-on experience in applying software frameworks for UI development and supporting senior engineers in creating efficient, user-friendly control and monitoring interfaces using Qt, Python, MATLAB, and LabVIEW.

Key Responsibilities :

Assist in developing user-friendly and responsive GUIs using Qt framework and Python libraries (PyQt, PySide)

Support creation of visualization dashboards and toolkits in MATLAB for signal processing, data analysis, and control systems

Work on LabVIEW-based interface development for instrumentation and hardware integration

Write and test UI code modules, scripts, and automation for prototype systems

Collaborate with embedded software and hardware engineers to integrate UI with backend systems

Participate in debugging, troubleshooting, and code reviews for UI components

Prepare basic documentation and user manuals for supported UI tools

Gain exposure to software design best practices, version control (Git), and software development life cycle

Assist in usability testing and gather user feedback to improve UI designs

Requirements :

Degree in Computer Science, Electrical Engineering, or related technical field

Basic proficiency in Qt framework and Python programming

Familiarity with MATLAB and LabVIEW environments preferred

Understanding of GUI design principles, event-driven programming, and software testing

Good analytical, problem-solving, and collaborative skills

Eagerness to learn software development tools and user interface design methodologies