junior software engineering Embedded Software Engineer ic Phd's · Posted Sep 12, 2025

About this role

Johns Hopkins APL is hiring a junior-level Embedded Software Engineer in the software engineering function based in Laurel, MD. The posting calls out experience with Python, C, TensorFlow, PyTorch. Listed education preference: a Ph.D. or equivalent.

Role
Embedded Software Engineer
Function
software engineering
Level
junior
Track
Individual contributor
Location
Laurel, MD
Education
Ph.D. preferred
Department
Electrical/Computer Engineering
Posted
Sep 12, 2025
AI Summary
Junior-level embedded software engineer developing wireless communications solutions using software-defined radios and machine learning for U.S. military and intelligence applications. Requires PhD in Electrical or Computer Engineering, expertise in signals/systems or wireless communications, and proficiency in Python, C++, C, VHDL/Verilog, or MATLAB. Must obtain Top Secret security clearance.

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Job description

from Johns Hopkins APL careers
Description

Do you want to become an expert in wireless communications?

 

Are you passionate about learning about the latest wireless technologies?

 

If you are graduating with a PhD in Electrical or Computer Engineering and want to work in wireless communications, we'd love to have you join our team!

 

We are seeking to develop engineers to help us give our nation a significant advantage by controlling the wireless communications environment. Our Wireless Cyber Capabilities team focuses on providing the U.S. military and intelligence communities with operational advantages by leveraging software-defined radios, commercial cellular equipment, and machine learning to develop advanced capabilities for research and operational prototypes. To learn more about our work, click here

 

Our engineers apply cutting-edge research to some of the government’s most critical challenges in the follow research areas:

 

Wireless Cybersecurity

  • We leverage our deep knowledge of wireless protocols to develop new and innovative approaches to secure our nation’s communications against on-network and off-network attacks.

 Radio Frequency Machine Learning (RFML)

  • We apply our expertise in deep learning to devise novel solutions to complex RF and wireless communications problems that are intractable using conventional approaches.

 Resilient Tactical Communications

  • We draw on our mastery of wireless networking and waveform design to fortify existing systems and design new systems that will enable robust, adaptable tactical communications.
  • This is an excerpt. Read the full job description on Johns Hopkins APL careers →
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