Wireless Protocol Software Engineer
Pubblicato il 12-09-2026 - Keysight Technologies in Italia
Overview
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.
Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
Keysight is looking for a recent graduate (MSc or PhD) in Telecommunications Engineering to join our R&D; team as a Wireless Protocol Software Engineer focused on Layer 2 (L2) .
This is an excellent opportunity to start your career working on cutting-edge 5G and emerging 6G technologies ,
contributing to real-world implementations of 3GPP protocol stacks used in advanced wireless test and emulation platforms.
You will work alongside experienced engineers in a collaborative, multi-site international environment , gaining hands-on experience in designing and developing high-performance protocol software .
Responsibilities
- Contribute to the design, development, and testing of Layer 2 protocol stack components :
- MAC (Medium Access Control)
- RLC (Radio Link Control)
- PDCP (Packet Data Convergence Protocol)
- Support development of UE and base station (gNB) emulation solutions
- Analyze and implement features from 3GPP LTE and 5G NR specifications
- Assist in translating requirements into:
- Clean and maintainable code
- Test cases and validation scenarios
- Collaborate with cross-functional teams ( systems, RF, protocol, software ) to:
- Investigate and debug protocol behavior
- Support issue analysis and resolution
- Participate in continuous learning of evolving s