Parallel Wireless
5G/LTE Network Engineer I
Greater Boston Area
Work authorization requiredDetected 103 days ago
PythonBashLinuxNetwork SecurityElectrical Engineering5G/LTENetwork EngineeringCommunication
About the role
- You will work across the full lifecycle of mobile network infrastructure from lab integration and commissioning through live deployment, performance monitoring, and ongoing optimization.
- One day you're tracing a signaling failure at the protocol level
- the next you're investigating why a cluster of cells is underperforming against their KPI targets.
Responsibilities
- Ability to read and interpret packet captures even if you're still building that skill
- As pioneers of Open RAN, we prioritize innovation, flexibility, and sustainability to help build a more connected, and green networks.
- Join us as we lead the future of telecommunications, driving innovation through green and sustainable networks.
Requirements
- A Bachelor's or Masters's degree in Telecommunications, Electrical Engineering, Computer Networks, or a related field, recent graduate or up to 1 year of experience
- Comfort working in Linux environments from the command line
- Clear written and verbal communication: your analysis is only as good as your ability to explain it
- Ability to travel internationally as needed
Benefits
- Learn more about our mission, vision and values.
Company info
- Headquartered in the USA with global R&D centers, we are proud to serve over 60 customers worldwide and have been recognized with over 100 industry awards.
- Our mission is to accelerate GSMA's Mobile Net Zero initiative by reducing TCO and driving innovation across the telecom ecosystem.Learn more at www.parallelwireless.com.
- We are committed to building inclusive and diverse teams representing all backgrounds, with a wide range of perspectives, and empowering industry-leading skills.
Visa & Work Authorization
- Be authorized to work in the U.S. without sponsorship
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This listing is sourced directly from Parallel Wireless's careers page and normalized into a canonical job model.