Embedded Systems Design Engineer

Johns Hopkins Applied Physics Laboratory•Laurel, MD

1d•Onsite

About The Position

We are seeking an Embedded Systems Design Engineer to help us build innovative technology applications for the next generation of electronic warfare (EW) systems. Your work will contribute to ensuring the US and its allies dominate the RF spectrum. You 'll be joining our hardworking team of system engineers, algorithm developers, FPGA and embedded software engineers, and advanced EW technology enthusiasts who enjoy working together to craft creative solutions to complex challenges in addition to bringing real solutions from concept to prototyping.

Requirements

Have a Bachelor's degree in Electrical Engineering, Computer Engineering, or a closely related technical field.
Have experience with MATLAB, C/C++, Python, or similar programming languages.
Have relevant experience working with embedded systems and embedded programming.
Have general knowledge of embedded systems design with FPGAs.
Are able to obtain an Interim Secret level security clearance by your start date, and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

Nice To Haves

Have a Master's degree in Electrical Engineering or Computer Engineering.
Have at least seven years of relevant experience working with embedded systems and embedded programming.
Have experience with VHDL, Verilog, or other FPGA development languages.
Have experience in programming for Software Defined Radio (SDR).
Are experienced with high-speed FPGA design.
Are experienced with digital signal processing (DSP) algorithms.
Hold an active DoD Secret level clearance or higher.

Responsibilities

Develop software and firmware for real-time embedded systems.
Implement digital signal processing (DSP) algorithms for various types of communication, data link, radar, and jamming signals.
Integrate embedded systems with EW payloads.
Apply Machine Learning (ML)/Artificial Intelligence (AI) algorithms for EW applications.
Test and demonstrate your work in field tests and lab demos.