Radar Algorithm Developer

IERUS participates in projects that seek to apply advanced machine-learning (ML) and artificial intelligence (AI) to our relevant domains of expertise. Past and present areas of expertise for application of ML/AI include:

• RADAR

• Signal processing, system design, operational optimization, detection, discrimination, and tracking

• RF/EO/IR

• Signal processing, system design, signatures, tracking, and testing

• Electronic Warfare (EW)

• System design, research, testing, counter-measures

• Antennas

• System design and testing

• Image processing

• Segmentation, recognition, and denoising

• Critical infrastructures

• Process control systems, situational awareness, cyber security, anomaly detection

• Vehicles and vessels

• Situational awareness, cyber security, anomaly detection

• ML/AI R&D

• Algorithm development, GPU acceleration, global and local optimization of complex and fused data, adversarial ML, network architecture and computability

• MS degree in Electrical Engineering, Computer Science, Applied Mathematics, Statistics, or related field, plus 2+ years of experience in applying engineering solutions featuring AI/machine-learning, to the problem types described above
• OR: BS degree in Electrical Engineering, Computer Engineering, or Computer Science plus 3+ years' experience in applying engineering solutions featuring AI/machine-learning, to the problem types described above, * Must be a U.S. citizen;
• Active Secret security clearance, preferred TS clearance and TS/SCI opportunities;
• Experience implementing machine learning solutions for engineering and scientific domains. Should be familiar with related implementation tasks such as feature selection, regression, classification, sensor-fusion, time-series analysis, missing data, optimization, recommender systems, etc.;
• Mastery of rapid prototyping in at least 1 (preferably 2 or more) of the following scripting languages: Python, R, MATLAB, etc.;
• Experience implementing solutions using at least 2 of the following supervised methods: SVM/SVR, fuzzy systems (TSK, etc.), tree ensemble methods (Bayesian, bagging, boosting, etc.), NNs (supervised), others;
• Experience applying advanced math and statistics, especially optimization and related linear algebra techniques.

Preferred Qualifications:

• PhD in Electrical Engineering, Computer Science, Computer Engineering or related field;
• Proficiency in at least 1 hard programming language (C/C++, Java, etc.);
• Experience implementing solutions using any of the following unsupervised methods: Clustering (k-nearest neighbor, DBSCAN, Dirichlet, etc.), autocorrelation, Deep learning methods (DNNs, CNNs, RNNs, LSTMs, etc.) and packages (TensorFlow, Theano, Torch, Caffe, Neon, etc.), GMMs, HMMs, etc.;
• Experience with Government funding agencies and programs (e.g. DARPA, IARPA, AFRL, SBIR/STTR, RiF, etc.);
• Publication and/or patent history of applying original solutions to relevant types of problems;
• Experience implementing solutions using signal processing algorithms and packages;
• TS/SCI clearance;
• Engineering experience in the defense industry;
• Image processing experience;
• Radar system analysis experience;
• RF Electronics experience;
• Antenna design and analysis experience;
• Software Defined Radio (SDR) experience;
• Analysis tool-building experience;
• Target acquisition, tracking and/or algorithm development;
• Advanced modeling skills and optimization;
• Knowledge of domain specific RADAR principles, including signal processing, RCS analysis, target acquisition; target tracking, resource management, discrimination, and battle manager interfaces; and / or
• Experience with GMD/BMDS systems, BMDS radar systems, radar simulation tests and or radar metrics.