Title:
RF MASINT Engineering SME
Belong. Connect. Grow. with KBR!
KBR’s National Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and national security communities. In this position, your work will have a profound impact on the country’s most critical role – protecting our national security.
KBR is seeking a self-motivated
KBR is seeking a self-motivated RF MASINT Engineering SME with an active TS/SCI clearance to develop MASINT algorithms and employ probability theories and computational methods to large datasets. These algorithms will be used to analyze and better understand threats to DoD interests. Candidate should have expert-level proficiency in MATLAB and require minimal oversight.
-Strong proficiency in probability theory and statistics
-Experience in the application of computational Bayesian methods, such as Markov-Chain Monte Carlo analyses (e.g., Metropolis-Hastings or Gibbs Sampling) and Variational Inference
-Understanding of numerical optimization techniques
-Graduate degree in Engineering, Applied Physics, Applied Mathematics, or extensive relevant experience in a related technical field
-Proficiency in MATLAB programming language
-Ability to work independently and with teams
-Must have an Active TS Clearance
-Experience in applied stochastic estimation (e.g., Kalman and nonlinear filtering)
-Basic understanding of classical mechanics and applications
-Proficiency in C/C++ and Python programming languages
-Proficiency in numerical mathematics techniques
-Understanding of high-performance computing and parallel algorithm design
-Experience with scientific data processing (including signal processing), modeling and simulation, and R&D algorithm development
with an active TS/SCI clearance to develop MASINT algorithms and employ probability theories and computational methods to large datasets. These algorithms will be used to analyze and better understand threats to DoD interests. Candidate should have expert-level proficiency in MATLAB and require minimal oversight.
-Strong proficiency in probability theory and statistics
-Experience in the application of computational Bayesian methods, such as Markov-Chain Monte Carlo analyses (e.g., Metropolis-Hastings or Gibbs Sampling) and Variational Inference
-Understanding of numerical optimization techniques
-Graduate degree in Engineering, Applied Physics, Applied Mathematics, or extensive relevant experience in a related technical field
-Proficiency in MATLAB programming language
-Ability to work independently and with teams
-Must have an Active TS Clearance
-Experience in applied stochastic estimation (e.g., Kalman and nonlinear filtering)
-Basic understanding of classical mechanics and applications
-Proficiency in C/C++ and Python programming languages
-Proficiency in numerical mathematics techniques
-Understanding of high-performance computing and parallel algorithm design
-Experience with scientific data processing (including signal processing), modeling and simulation, and R&D algorithm development
Belong, Connect and Grow at KBR
At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team’s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver – Together.
KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.
