- Architect and implement software solutions to resolve complex challenges
- Develop original custom software suites as well as plugins and patches for existing code
- Utilize debugging tools, analysis tools, and other capabilities to troubleshoot and fix complex software applications and libraries.
- Perform verification and validation at both the component/subsystem and system level.
- Design and implement solutions utilizing query languages and data mining tools for database interaction and multi-source data integration.
- Must have a current/active TS/SCI & Polygraph (some positions do not require clearances)
- Minimum experience with BS in Computer Engineering, Electrical Engineering, Computer Science, Applied Mathematics, Aerospace Engineering or relevant science or engineering discipline.
- Experience with a wide range of programming efforts: network programming, hardware/software communications, database queries, image processing, embedded programming, desktop applications
- Experience with digital signal processing
- Proficient in one or more of the following languages: C/C++, Java, C#, Python, HTML/Java Script
- Demonstrate an understanding of client/server, web-based, and server-side computing architectures focusing on metadata mining concepts.
- Knowledge of and experience with implementation of the full software development life cycle.
- Proficiency in the following: hardware and software design, software modeling, systems-level software testing, high consequence anomaly resolution and deployment of delivered systems.
- Experience with relevant application and mission domains (ground systems/data centers/operations centers, remote sensing, senor technologies, proliferation detection, monitoring and surveillance).
- Proven ability to construct and utilize modeling, simulation, and probability & statistics to predict, quantify, qualify results in numerical analysis languages and tools (Matlab, X-Midas, IDL, R, etc).
- Experience with FPGA architectures and/or embedded software development for real-time systems.
- Creativity and strong problem solving skills in utilizing data science and data analytic frameworks and applications including supervised and unsupervised classification, machine learning, applied statistics, and other skills.