Senior Open RAN Digital Twin & AI Simulation Engineer

parallel wireless; United States; Remote; USD 140,000 - 220,000; Full time

Job summary

Parallel Wireless, a U.S.-based Open RAN pioneer, seeks a senior wireless systems engineer to lead a multi-RAT digital twin for LTE, 5G NR, and 2G, driving model fidelity and production-ready simulation for feature development and validation.

You will evolve an LTE end-to-end simulator into a scalable platform, integrating MAC/scheduler software, and enabling AI/ML-driven RAN capabilities. This is a hands-on role with impact across RAN stack teams.

Qualifications

• Proficient in C/C++ and Python with integration to simulation tools.
• Experience building or validating link-level/system-level simulations.
• Strong Linux development background with Git, containers, and CI/CD.

Responsibilities

• Own the architecture and roadmap for a modular multi-RAT RAN digital twin.
• Integrate production MAC and scheduler software into deterministic simulations.
• Model interactions among scheduler, PHY, channels, and mobility in LTE/5G/2G stacks.
• Extend LTE simulations to support 5G NR and 2G without duplicating platform work.
• Design a fidelity ladder with high-fidelity PHY and fast surrogate models.
• Develop AI/ML-based RAN capabilities and evaluation pipelines.
• Create reproducible experiments with clear KPIs and calibration rules.
• Establish verification and validation practices with lab-vs-sim matching.
• Build automated tests and CI/CD integration for QA.

Skills

C/C++

Python

Linux

CI/CD

MATLAB

Git

Machine Learning

Open RAN

Education

BSc in Electrical/Computer Engineering

MSc in Electrical/Computer Engineering

PhD (nice to have)

Tools

PyTorch

TensorFlow

NumPy/SciPy

MATLAB

Job description

Parallel Wireless, a U.S.-based Open RAN pioneer, seeks a senior wireless systems engineer to lead a multi-RAT digital twin for LTE, 5G NR, and 2G, driving model fidelity and production-ready simulation for feature development and validation.

You will evolve an LTE end-to-end simulator into a scalable platform, integrating MAC/scheduler software, and enabling AI/ML-driven RAN capabilities. This is a hands-on role with impact across RAN stack teams.