Senior/Principal RAN Digital Twin & AI Simulation Engineer

parallelwireless; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Parallel Wireless, a U.S.-based Open RAN pioneer, seeks a senior wireless systems engineer to lead the development of a multi-RAT digital twin for our Open RAN solution. You will evolve an LTE end-to-end simulator into a scalable platform supporting feature development, regression testing, and performance optimization.

The role focuses on fast, trustworthy simulations across MAC, PHY, channel, and network models, with use cases including MAC scheduler improvements, power control, mobility,

Qualifications

• Senior individual-contributor role at the intersection of wireless systems, simulation, production software, and AI/ML.
• Develop and evolve LTE end-to-end simulator into a scalable platform for feature development, regression testing, performance optimization, and pre-validation.
• Initial use cases include MAC scheduler and link-adaptation improvements, power control, mobility and interference scenarios, and neural-network-assisted channel estimation.

Responsibilities

• Lead the development of a multi-RAT digital twin for Open RAN.
• Evolve existing LTE end-to-end simulator into a scalable engineering platform.
• Calibrate the twin against lab or field data with multiple fidelity levels.

Job description

Parallel Wireless is a U.S.-based pioneer in Open RAN innovation, transforming how mobile networks are built, optimized, and powered. Through our GreenRAN portfolio, we help operators deliver secure, energy-efficient, automated, and flexible connectivity across 2G, 3G, 4G, 5G, and the path toward 6G. Our software-centric, hardware-agnostic approach brings intelligence into the RAN while helping customers reduce complexity and total cost of ownership.

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.