- Parallelwireless
- United States,
- Full-Time
- 17 days ago
Senior/Principal RAN Digital Twin & AI Simulation Engineer.
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Senior/Principal RAN Digital Twin & AI Simulation Engineer: our view in 3 lines...
- The Role:This role is for a senior wireless systems engineer building a multi-RAT digital twin for Open RAN simulation and pre-validation.
- The Person:The person will design and extend a multi-RAT RAN digital twin, integrate production MAC and scheduler software into simulations, build datasets and experiments, and establish verification, validation and regression testing practices.
- Requirements:The ideal candidate has 7+ years of experience, strong programming skills in C or C++ and Python, scientific computing with NumPy, SciPy and pandas, and experience with Linux, Git, automated testing and CI/CD.
About the role
Parallel Wireless is looking for a hands-on wireless systems engineer to lead the development of a multi-RAT digital twin for our Open RAN solution. The digital twin will execute production RAN software-beginning with scheduler and MAC behavior-in a closed loop with PHY, channel, UE, traffic, and network models. It will allow engineering teams to design, evaluate, and compare features for LTE, 5G NR, and 2G without requiring a dedicated physical radio setup for every development cycle.
This is a senior individual-contributor role at the intersection of wireless systems, simulation, production software, and AI/ML. You will evolve an existing LTE end-to-end simulator into a scalable engineering platform for feature development, regression testing, performance optimization, and evidence-based pre-validation. Initial use cases include MAC scheduler and link-adaptation improvements, power control, mobility and interference scenarios, and neural-network-assisted channel estimation.
The successful candidate will understand that a useful digital twin must be both fast and trustworthy. You will define multiple fidelity levels-from rapid surrogate models to full PHY processing-and establish repeatable methods for calibrating the twin against lab or field reference data. The goal is to reduce dependence on continuous lab access while maintaining clear, measurable confidence in the simulation results.

