Principal RF/DSP Engineer

• →Take ownership of our most difficult unfamiliar RF targets with no prior framing: generate hypotheses, rank them, and design the experiment plan that discriminates between them.
• →Analyze wideband complex-IQ recordings from known and unfamiliar RF systems.
• →Characterize signal bandwidth, timing, modulation, synchronization, channel access, frequency-hopping behavior, framing, coding, and other observable properties.
• →Design controlled experiments that isolate transmitter behavior and reveal waveform or protocol structure, and decide when a line of investigation should be redirected or abandoned.
• →Develop algorithms for burst detection, synchronization, demodulation, signal characterization, protocol recovery, classification, and tracking.
• →Design, implement, and own reusable signal-processing components — synchronization libraries, synthetic-waveform and impairment-injection frameworks, replay fixtures, and validation harnesses — used across the team.
• →Own and improve line-of-bearing performance: develop and refine array signal-processing algorithms for bearing estimation (e.g., correlative interferometry, subspace methods such as MUSIC, beamforming), and quantify accuracy against ground truth.
• →Diagnose and mitigate real-world DF error sources including array calibration drift, mutual coupling, channel phase/gain mismatch, multipath, platform and mast effects, and coherent-source conditions.
• →Design array calibration procedures and validate them in conducted, anechoic/open-range, and field settings.
• →Distinguish target signals from noise, interference, receiver artifacts, and benign emitters in dense RF environments.
• →Implement and optimize production DSP capabilities in modern C++.
• →Convert exploratory analysis into maintainable, observable, and computationally bounded production components.
• →Validate algorithms using synthetic, conducted, over-the-air, and field-recorded data, and lead field validation campaigns.
• →Measure detection probability, false-alarm rate, packet error rate, acquisition behavior, latency, and computational performance.
• →Diagnose failures involving CFO, sample-clock error, timing recovery, multipath, clipping, IQ imbalance, spectral inversion, dropped samples, and interference.
• →Serve as day-to-day technical lead for other signal-processing engineers: review their analysis, experiment designs, and code; de-risk their approaches; and step into stalled efforts and get them moving.
• →Identify emerging target classes and systemic bottlenecks, and recommend technical investments to leadership.
• →Work with RF, FPGA, embedded software, data science, test, and mission teams.
• →Document observations, assumptions, confidence levels, known limitations, and recommended next experiments.

This position requires access to information that is subject to compliance with the International Traffic Arms Regulations (“ITAR”) and/or the Export Administration Regulations (“EAR”). In order to comply with the requirements of the ITAR and/or the EAR, applicants must qualify as a U.S. person under the ITAR and the EAR, or a person to be approved for an export license by the governing agency whose technology comes under its jurisdiction. Please understand that any job offer that requires approval of an export license will be conditional on AeroVironment’s determination that it will be able to obtain an export license in a time frame consistent with AeroVironment’s business requirements. A “U.S. person” according to the ITAR definition is a U.S. citizen, U.S. lawful permanent resident (green card holder), or protected individual such as a refugee or asylee. See 22 CFR § 120.15. Some positions will require current U.S. Citizenship due to contract requirements.

Benefits:  AV offers an excellent benefits package including medical, dental vision, 401K with company matching, a 9/80 work schedule and a paid holiday shutdown.  For more information about our company benefit offerings please visit:  http://www.avinc.com/myavbenefits.

We also encourage you to review our company website at http://www.avinc.com to learn more about us.

Principals only need apply.  NO agencies please.

About AV:

AV isn’t for everyone. We hire the curious, the relentless, the mission-obsessed. The best of the best.

We don’t just build defense technology—we redefine what’s possible. As the premier autonomous systems company in the U.S., AV delivers breakthrough capabilities across air, land, sea, space, and cyber. From AI-powered drones and loitering munitions to integrated autonomy and space resilience, our technologies shape the future of warfare and protect those who serve.

Founded by legendary innovator Dr. Paul MacCready, AV has spent over 50 years pushing the boundaries of what unmanned systems can do. Our heritage includes seven platforms in the Smithsonian—but we’re not building history, we’re building what’s next.

If you're ready to build technology that matters—with speed, scale, and purpose—there’s no better place to do it than AV.

We are proud to be an EEO/AA Equal Opportunity Employer, including disability/veterans. AeroVironment, Inc. is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Qualified applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, protected veteran status, genetic data, sexual orientation, gender identity or other legally protected status.

ITAR

• BS or higher in Electrical Engineering, Computer Engineering, Applied Physics, or a related technical field.
• Substantial professional experience developing RF, communications, radar, electronic-warfare, or related signal-processing systems.
• Strong DSP and digital-communications fundamentals, including several of the following: Sampling and aliasing; Digital downconversion; FIR/IIR and multirate filtering; FFT and time-frequency analysis; Matched filtering; Detection and estimation; Carrier, phase, symbol-timing, and frame synchronization; Modulation and demodulation; Channel coding and error detection.
• Demonstrated ability to independently investigate an unfamiliar signal or system using measurements and controlled experiments, from initial hypothesis through validated conclusion.
• Experience analyzing real complex-IQ data—not only simulations or high-level system models.
• Hands-on experience implementing, testing, and debugging DSP algorithms.
• Proficiency writing production-quality C++ in a Linux environment.
• Hands-on experience with direction finding and antenna-array signal processing: bearing estimation on real multichannel data (interferometric, beamforming, or subspace methods), array calibration, and an understanding of practical DF error sources such as mutual coupling, channel mismatch, and multipath.
• Experience creating automated tests and replaying recorded data through algorithm pipelines.
• Experience with collaborative source control and code review using Git or an equivalent system.
• US Citizenship is required.

• Track record of independently reverse-engineering an undocumented or partially documented wireless waveform or protocol through to a fielded or productized capability.
• Demonstrated technical leadership of other engineers: reviewing designs and code, setting methodology, and raising team output while remaining hands-on.
• Experience designing reusable DSP libraries, frameworks, or test infrastructure adopted by other engineers.
• Experience with Software Defined Radios, RF laboratory equipment, and conducted or over-the-air testing.
• Experience with frequency-hopping, spread-spectrum, OFDM, cellular, telemetry, command-and-control, or other modern communication systems.
• Experience building detectors that operate in congested RF environments with measurable false-alarm requirements.
• Experience with FPGA-based DSP, fixed-point implementation, hardware/software partitioning, or high-rate sample transport.
• Experience optimizing real-time C++ DSP pipelines using profiling, SIMD, threading, bounded queues, and reusable buffers.
• Experience generating synthetic waveforms and injecting controlled impairments such as noise, CFO, clock offset, fading, and interference.
• RF antenna design experience: element or array design, simulation (e.g., HFSS, CST, FEKO), pattern and impedance measurement, or working directly with antenna engineers on array geometry and platform integration trades.
• Deeper array-processing experience: wideband DF, DF on frequency-hopping or short-burst emitters, coherent multichannel receiver architectures, or emitter geolocation (TDOA/AOA fusion, multi-sensor triangulation).
• Familiarity with statistical classification or machine learning applied to RF data.
• Experience with Counter-UAS, electronic warfare, SIGINT, radar, or related mission systems.

• Take full ownership of a novel, undocumented RF target with no prior framing, and independently produce a credible hypothesis set and experiment plan.
• Demonstrate a detector, demodulator, or protocol feature against recorded IQ, and carry it into the production C++ architecture with positive, negative, and regression tests.
• Quantify performance, communicate known limitations, and lead validation against additional devices, environments, and RF conditions — including running a field campaign.
• Assess the current line-of-bearing capability against ground-truth data, identify the dominant error sources, and land at least one measurable accuracy or robustness improvement.
• Measurably raise the output of other signal-processing engineers: unblock at least one stalled effort, and have their reviews and methodology visibly improve others' work.
• Surface at least one emerging target class or systemic bottleneck with a concrete, prioritized recommendation.

The strongest candidate may come from communications, SDR, FPGA, radar, telemetry, electronic warfare, or protocol-analysis work. Exact domain overlap matters less than demonstrated ability to:

1. Learn an unfamiliar signal from first principles, without a framing handed to them.
2. Design experiment campaigns rather than guess — and know when to kill a dead-end thread.
3. Work directly with imperfect real-world data.
4. Turn analysis into reliable production code and reusable components others build on.
5. Validate claims quantitatively and defend them in review.
6. Make the engineers around them better while remaining hands-on through integration and field testing.