Mid-Level Research Engineer ( R-00072827 )
The Leidos Innovations Center (LInC) has an exciting opportunity for a skilled Research Engineer to be part of a strong team of scientists, engineers and operations experts addressing some our nation’s most challenging intelligence problems. Come join a team conducting applied research and development, including the development and assessment of signal processing and machine learning algorithms against real-world data. The division’s primarily focus is on research and development and advanced prototyping.
- Be part of a small team that analyzes signatures from MASINT targets embedded in challenging interference environments in order to identify exploitable features and develop detection, classification and geolocation algorithms that generate valuable information for intelligence analysts.
- Participate in customer-sponsored field tests, signal modeling for operational planning, and building and testing commercial off-the-shelf (COTS) systems, such as software-defined radios (SDRs), for use in prototype signal collection and processing systems.
- Development of digital signal processing algorithms and analysis tools, incorporating traditional Signal Processing as well as Machine Learning (ML) and Artificial Intelligence (AI) techniques applied to Signal Processing; conducting data processing and analysis; performing signal detection, characterization and geolocation operations; and implementing algorithms in hardware systems as research progresses toward operational implementation.
- Bachelor’s degree in Electrical Engineering, Computer Science, Physics, Mathematics or a related field, with 4-8 years of relevant work experience, or a Master’s degree in these same fields with 2-6 years of relevant work experience
- Be capable of implementing and/or developing basic signal processing and machine learning algorithms based on a literature search or technical description of a signature
- Experience with some or all of the following programming languages: MATLAB, Python, C, C++
- Strong analytical skills in the areas of detection and estimation theory, machine learning, adaptive filter theory, spectral estimation, linear algebra and/or stochastic processes (all are not required)
- Capable of working in a small team environment, to include providing data collection and analysis support at customer sponsored field tests
- An entrepreneurial, motivated, self-starter attitude