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.

IERUS specializes in technology research, testing, and implementation with core competencies in electromagnetics phenomenology, computational analytics (algorithm acceleration and machine learning), and weapon system engineering. IERUS develops value for our defense and commercial customers through accelerations of the technology life cycle: identifying, creating, transitioning, and producing technologies with integrity of purpose and product. IERUS offers competitive compensation packages, retirement options, and benefits packages. To learn more, please visit www.ierustech.com.

IERUS participates in projects that address weapon systems engineering and the application of advanced machine learning (ML) and artificial intelligence (AI) techniques as well as RF/Optical hardware prototyping and low rate production. We generally seek to apply agile development fundamentals across our corporate portfolio to accelerate technology development timelines. The end goal being early discovery, accelerated development, and high customer engagement.