Senior Research Scientist - Network Systems

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.

• Strong foundation in RF communications theory, including modulation/demodulation, propagation, link budgets, and spectrum analysis
• Hands-on experience with digital signal processing (DSP) — filtering, FFT/spectral analysis, detection, estimation, and adaptive algorithms
• Demonstrated expertise in compressive sensing, including sparse signal recovery, L1/L2 optimization, sensing matrix design, and sub-Nyquist sampling techniques

• Proficiency designing and implementing ML algorithms (supervised, unsupervised, deep learning, reinforcement learning) with emphasis on signal/time-series data
• Experience building end-to-end ML pipelines — data ingestion, preprocessing, feature engineering, training, validation, deployment, and monitoring
• Knowledge of ML architectures including CNNs, RNNs/LSTMs, transformers, autoencoders, and GANs, with applied experience selecting the right model for RF/signal and data analytic problems
• Strong data analytics skills: exploratory analysis, statistical modeling, visualization, and deriving actionable insight from large/complex datasets
• Hands-on with frameworks such as PyTorch, TensorFlow/Keras, scikit-learn, and data tooling (NumPy, pandas, Spark)
• Experience with MLOps practices — version control, containerization (Docker), CI/CD, experiment tracking (MLflow, W&B), and model serving

• Strong programming skills in Python and C/C++; MATLAB a plus
• Version control (Git), Linux development environment, and scripting proficiency

• BS in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, or related discipline and a minimum of 12 years of experience; Minimum of 10 years with MS/MA; Minimum of 7 years with Ph.D.
• Demonstrated project or publication record spanning both RF/signal processing and machine learning domains
• US Citizenship

• Experience applying ML to RF problems: signal classification, spectrum sensing, RFI mitigation, cognitive radio, direction finding, or emitter identification
• Background in DoD / IC programs, EW, SIGINT, or radar systems
• Active security clearance (or ability to get one)

• Clear technical communication — able to translate algorithms to implementation and results to stakeholders, and write technical papers and reports
• Self-directed, with experience taking prototypes from concept through demonstration

$146,000 - $234,000. 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.

The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. By applying to this job, you are expressing interest in the role and the Company. During the review of your application, you may be required to participate in an on-camera interview, as well as participate in a process to verify your identity. Use of artificial intelligence (AI) tools of any kind during Peraton interviews is strictly prohibited unless the candidate has obtained prior written authorization. All interview responses must be the candidate’s own.

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