Research Scientist - RF Machine Learning

Peraton; College Park (MD); On-site; USD 135,000 - 216,000; Full time

Benefits offered by this job

Increased sign-on bonus eligibility

Job summary

Peraton is seeking a Senior Research Scientist specializing in RF Machine Learning for its Maryland site. The role requires expertise in leading the design and evaluation of RF algorithms, working on projects that transition from research to prototyping. Candidates must have significant experience in machine learning frameworks, digital signal processing, and programming in Python. This position is on-site in College Park MD, catering to interests in wireless technologies and requires a TS/SCI w/ Polygraph clearance.

Qualifications

• Minimum of 6+ years of experience with a Bachelor's degree, 4+ years with a Master's, or 2+ years with a Ph.D.
• Strong background in RF machine learning and digital signal processing.
• Experience working in Linux-based development environments.

Responsibilities

• Lead the design, development, prototyping, and evaluation of RF/ML algorithms.
• Research and implement machine learning approaches for RF signal detection.
• Communicate research findings and technical approaches through technical reports.

Skills

Radio frequency Machine Learning

Digital signal processing

Wireless communications

Programming in Python

Machine learning frameworks (PyTorch, TensorFlow)

Education

Bachelor's degree in Electrical Engineering or related field

Master's degree in relevant discipline

Ph.D. in applied Mathematics or Physics

Tools

MATLAB

GNU Radio

C/C++

Job description

Research Scientist - RF Machine Learning

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.

Key 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

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.

Qualifications

Minimum Qualifications

• 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

Desired Additional Qualifications

• 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

Target Salary Range

$135,000–$216,000

EEO

Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.