Research Scientist - RF Machine Learning

Peraton•College Park, MD

1d•Onsite

About The Position

Peraton Labs is seeking a poly cleared Senior Research Scientist to support cleared research and development efforts for a Maryland-based IC customer. This role will focus on leading the design, development, prototyping, and evaluation of RF Machine Learning algorithms and signal processing techniques for advanced wireless, spectrum, cyber, and communications research. You’ll work on mission-focused R&D efforts that move from research concepts to working prototypes and operationally relevant capabilities. You will collaborate with researchers, software engineers, signal processing experts, and customer stakeholders to solve complex problems involving RF sensing, signal characterization, waveform analysis, spectrum awareness, and machine learning-enabled wireless systems. This position requires full-time on-site work at a customer site near College Park, MD.

Requirements

Minimum of 6+ years of experience with a Bachelor’s degree, 4+ years of experience with a Master’s degree, or 2+ years of experience with a Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related discipline. In lieu of a Bachelors, an additional 4 years of experience is required for a total of 10+ years.
Strong background in Radio frequency Machine Learning, digital signal processing, wireless communications, or RF systems research
Experience designing, developing, training, testing, or evaluating machine learning models for RF, wireless, spectrum, signal processing, or communications applications
Experience with modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, or similar tools
Strong Experience programming in Python and at least one additional language such as C/C++, Java, or similar
Experience working with RF data, signal captures, IQ samples, simulated waveforms, or real-world wireless datasets
Experience working in Linux-based dev environments
Ability to develop, test, troubleshoot, document, and demonstrate research prototypes
Strong written and verbal communication skills, including the ability to present technical concepts and research results to technical stakeholders
US Citizenship is a requirement for this position
This position requires an active/current TS/SCI w/ Polygraph

Nice To Haves

Advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field is preferred
Demonstrated history of research in Machine Learning and RF spectrum domains, including publications, prototypes, proposals, patents, technical reports, or customer-facing research briefings
Experience with RFML applications such as signal classification, modulation recognition, emitter identification, spectrum sensing, anomaly detection, interference detection, protocol inference, or RF fingerprinting
Experience with SDR platforms such as Ettus USRP, HackRF, BladeRF, LimeSDR, or similar hardware
Familiarity with SDR software and RF development tools such as GNU Radio, UHD/USRP, MATLAB, Simulink or similar tools
Experience with wireless systems or protocols such as LTE, 5G, Wi-Fi, SATCOM, MANET, tactical radio systems, mesh networks, or custom waveform environments
Experience with RF test equipment such as spectrum analyzers, signal generators, oscilloscopes, vector signal analyzers, channel emulators, or RF front-end equipment
Experience with deep learning approaches for signal processing, including CNNs, RNNs, transformers, autoencoders, contrastive learning, self-supervised learning, or generative models
Experience with data engineering for RFML, including dataset generation, augmentation, labeling, synthetic data, simulation, model evaluation, and experiment tracking
Experience with tools such as NumPy, SciPy, Pandas, cuSignal, CUDA, MLflow, Weights & Biases, DVC, or similar tools
Experience integration ML models into deployable prototypes, edge systems, containers, testbeds, or cyber/radio experimentation environments
Experience with RF cyber research, wireless security, electronic warfare, spectrum operations, protocol reverse engineering, or adversarial ML
Ability to serve as a technical lead, task lead, or principal investigator on DoD/IC research efforts

Responsibilities

Lead the design, development, prototyping, and evaluation of RF/ML algorithms for wireless, spectrum, and communications applications
Research and implement machine learning approaches for RF signal detection, classification, characterization, anomaly detection, emitter identification, spectrum sensing, or waveform analysis
Develop and evaluate algorithms using modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, JAX, or similar tools
Apply strong digital signal processing and RF domain knowledge to develop, train, test, and validate models against real-world or simulated RF data
Design data collection, labeling, preprocessing, feature extraction, training, evaluation, and experimentation workflows for RFML research
Develop software prototypes using Python, C/C++, MATLAB, GNU Radio, or similar tools
Analyze RF signals, wireless protocol behavior, modulation characteristics, channel effects, interference, noise, and system performance
Work with RF datasets, signal captures, IQ data, SDR platforms, and lab or field-collected spectrum data
Support integration of RFML capabilities into larger research prototypes, testbeds, cyber experimentation platforms, or operationally relevant systems
Communicate research findings, technical approaches, experiment results, and prototype capabilities through customer briefings, technical reports, whitepapers, and publications
Provide technical leadership, mentor junior researchers or engineers, and help shape future RFML research direction