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P462 is seeking a full-time Sensor Systems Engineer with experience in the practical application of machine and deep learning. The individual will join the Sensor Systems & Battle Management, Command and Control (BMC2) department in applying novel Machine Learning/Deep Learning (ML/DL) technologies from across industry and academia to a variety of our nation's most critical sensing challenges.
* Apply knowledge of machine/deep learning, signal processing, and sensor systems engineering to challenging national security problems
* Support projects developing, applying and evaluating state-of-the-art algorithms/approaches for sensor systems.
* Develop and execute internal research in the area of machine/deep learning, signal processing, and sensor system analysis.
* Help grow P462's expertise in machine/deep learning.
Signal processing, detection and estimation theory, stochastic processes, numerical methods, linear algebra, applied statistics, probabilistic reasoning, graphical models, etc.
Algorithm development, quantitative data analysis, and modeling and simulation of physical systems.
Strong software development skills with experience using analytical software tools such as Python, C/C++, or MATLAB.
Proactive self-starter with strong analytical, problem solving, communication, and interpersonal skills.
Experience leading cross-disciplinary technical teams.
Experience managing R&D projects.
Knowledge of machine/deep learning techniques for pattern recognition in sensor data.
Familiarity with supervised/unsupervised learning processes, performance evaluation, validation and experiment design.
Ability to produce quantitative analysis benchmarking the performance of machine and deep learning algorithms/approaches against state-of-the-practice methods.
Processing data collected from one or more sensing modes such as radar, SONAR, EO/IR imagers, wireless communications, etc.
Familiarity with parsing, reduction, analysis, and visualization of data.
Hands-on experience applying machine/deep learning libraries such as SciPy, Scikit-Learn, TensorFlow, Torch, Keras, Spark, etc.
Ability to present technical briefs to potential sponsors.
B.S Degree in math, physics, engineering, or related disciplines.
M.S. or Ph.D in math, physics, engineering, or related disciplines with 3 years of experience working technical challenges associated with the application of deep/machine learning technologies to sensing applications.