Join our Team

About this opportunity:

As a Software Developer – Radio, you will help build next-generation radio platforms that enhance system stability, energy performance, and overall customer experience.The team values execution excellence, accountability, open communication, and a culture where engineers are encouraged to innovate and challenge norms.

What you will do:

• Develop, integrate, and test radio software for new and existing remote radio platforms, working across embedded and/or application layers.
• Contribute high-quality, maintainable code in C/C++/Java as part of a cross-functional R&D team.
• Analyze and resolve complex issues spanning software and hardware domains, driving problems to closure in close collaboration with peers and stakeholders.
• Apply AI/ML techniques and automation tools (e.g., TensorFlow or PyTorch–based solutions) to improve development efficiency, testing, diagnostics, and system performance.
• Participate in system integration and end-to-end validation to ensure high stability, reliability, and energy performance of radio products.
• Continuously refine design and implementation, contributing ideas that enhance architecture, code quality, and engineering workflows

The skills you bring:

• Master's degree in Telecommunications, Electrical Engineering, Electronic Information, Computer Science, Software Engineering, or a related field.
• Solid experience in Radio software design and/or testing, preferably in telecom or related domains.
• Strong programming skills in C/C++/Java, with a track record of delivering high-quality, production-grade code.
• Background in embedded software and/or application-level software development for complex systems.
• Basic understanding of AI/ML concepts (e.g., CNN, DNN, reinforcement learning) and hands-on exposure to frameworks such as TensorFlow or PyTorch.
• Practical or theoretical knowledge in AI/ML, with interest in applying it to embedded systems, radio optimization, or automation is a plus.
• Fluent English and strong communication skills, with a proactive, accountable working style in cross-functional environments.
• Motivation to learn on the job in areas such as radio product development, system integration, cross-team collaboration, stakeholder management, and practical use of AI tools for engineering efficiency.