Research Scientist - RF Machine Learning

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    "datePosted": "2026-05-11T04:00:00.000Z",
    "description": "<h2>Responsibilities</h2>\n<p><strong>Peraton Labs</strong> is seeking a poly cleared <strong>Senior Research Scientist</strong> 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.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p><strong><u>This position requires full-time on-site work at a customer site near College Park, MD.</u></strong></p>\n<p> </p>\n<p><strong><u>Key responsibilities may include</u></strong></p>\n<ul>\n <li>Lead the design, development, prototyping, and evaluation of RF/ML algorithms for wireless, spectrum, and communications applications</li>\n <li>Research and implement machine learning approaches for RF signal detection, classification, characterization, anomaly detection, emitter identification, spectrum sensing, or waveform analysis</li>\n <li>Develop and evaluate algorithms using modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, JAX, or similar tools</li>\n <li>Apply strong digital signal processing and RF domain knowledge to develop, train, test, and validate models against real-world or simulated RF data</li>\n <li>Design data collection, labeling, preprocessing, feature extraction, training, evaluation, and experimentation workflows for RFML research</li>\n <li>Develop software prototypes using Python, C/C++, MATLAB, GNU Radio, or similar tools</li>\n <li>Analyze RF signals, wireless protocol behavior, modulation characteristics, channel effects, interference, noise, and system performance</li>\n <li>Work with RF datasets, signal captures, IQ data, SDR platforms, and lab or field-collected spectrum data</li>\n <li>Support integration of RFML capabilities into larger research prototypes, testbeds, cyber experimentation platforms, or operationally relevant systems</li>\n <li>Communicate research findings, technical approaches, experiment results, and prototype capabilities through customer briefings, technical reports, whitepapers, and publications</li>\n <li>Provide technical leadership, mentor junior researchers or engineers, and help shape future RFML research direction</li>\n</ul>\n<p> </p>\n<p><em>*This position may be eligible for an increased sign-on bonus. Eligibility, bonus amount, and applicable terms and conditions will be discussed during the recruiting process*</em></p>\n<p> </p>\n<p><em>#MDFSP</em></p>\n<p>#PLABS26</p>\n<h2>Qualifications</h2>\n<p><strong><u>Minimum Qualifications</u></strong></p>\n<ul>\n <li>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.</li>\n <li>Strong background in Radio frequency Machine Learning, digital signal processing, wireless communications, or RF systems research</li>\n <li>Experience designing, developing, training, testing, or evaluating machine learning models for RF, wireless, spectrum, signal processing, or communications applications</li>\n <li>Experience with modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, or similar tools</li>\n <li>Strong Experience programming in Python and at least one additional language such as C/C++, Java, or similar</li>\n <li>Experience working with RF data, signal captures, IQ samples, simulated waveforms, or real-world wireless datasets</li>\n <li>Experience working in Linux-based dev environments</li>\n <li>Ability to develop, test, troubleshoot, document, and demonstrate research prototypes</li>\n <li>Strong written and verbal communication skills, including the ability to present technical concepts and research results to technical stakeholders</li>\n <li><strong><u>US Citizenship is a requirement for this position</u></strong></li>\n <li><strong><u>This position requires an active/current TS/SCI w/ Polygraph</u></strong></li>\n</ul>\n<p> </p>\n<p><strong><u>Desired Additional Qualifications</u></strong></p>\n<ul>\n <li>Advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field is preferred</li>\n <li>Demonstrated history of research in Machine Learning and RF spectrum domains, including publications, prototypes, proposals, patents, technical reports, or customer-facing research briefings</li>\n <li>Experience with RFML applications such as signal classification, modulation recognition, emitter identification, spectrum sensing, anomaly detection, interference detection, protocol inference, or RF fingerprinting</li>\n <li>Experience with SDR platforms such as Ettus USRP, HackRF, BladeRF, LimeSDR, or similar hardware</li>\n <li>Familiarity with SDR software and RF development tools such as GNU Radio, UHD/USRP, MATLAB, Simulink or similar tools</li>\n <li>Experience with wireless systems or protocols such as LTE, 5G, Wi-Fi, SATCOM, MANET, tactical radio systems, mesh networks, or custom waveform environments</li>\n <li>Experience with RF test equipment such as spectrum analyzers, signal generators, oscilloscopes, vector signal analyzers, channel emulators, or RF front-end equipment</li>\n <li>Experience with deep learning approaches for signal processing, including CNNs, RNNs, transformers, autoencoders, contrastive learning, self-supervised learning, or generative models</li>\n <li>Experience with data engineering for RFML, including dataset generation, augmentation, labeling, synthetic data, simulation, model evaluation, and experiment tracking</li>\n <li>Experience with tools such as NumPy, SciPy, Pandas, cuSignal, CUDA, MLflow, Weights & Biases, DVC, or similar tools</li>\n <li>Experience integration ML models into deployable prototypes, edge systems, containers, testbeds, or cyber/radio experimentation environments</li>\n <li>Experience with RF cyber research, wireless security, electronic warfare, spectrum operations, protocol reverse engineering, or adversarial ML</li>\n <li>Ability to serve as a technical lead, task lead, or principal investigator on DoD/IC research efforts</li>\n</ul>\n<h2>Peraton Overview</h2>\n<p>Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure.</p>\n<h2>Target Salary Range</h2>$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.\n<h2>EEO</h2>EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.",
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