Machine Learning Signal Processing Engineer

Description

Job Description:

Do you want to join a high performing team that values integrity, innovation, and collaboration with a company whose mission is to make the world safer, healthier, and more efficient through information technology, engineering and science? Are you interested making a difference by applying your machine learning and signal processing skills toward state-of-the-art research and development problems? Leidos currently has an exciting opening for a machine learning and signal processing engineer to work in our Beavercreek, Ohio office. 

As a machine learning / signal processing engineer, you will apply your skills to a wide variety of problems and datasets, primarily focused on remote sensing (Electronic Support Measures {ESM}, acoustic, RF, EO/ IR, and lidar) applications. Current projects include, but are not limited to, detection, tracking, data fusion, and classification. We develop a variety of combat identification (CID) algorithms and systems for both air and ground targets and specialize in technologies to train these systems on synthetic data. We are looking for a qualified candidate to bring technical excellence, leadership, entrepreneurship, and creativity to our programs. You will interact with customers, participate in and lead technical projects areas, and have the opportunity to pursue growth in new areas.  This position requires most job duties to be performed onsite due to the sensitive nature of this work and the desire for in-person collaboration, however we offer flexible in-office hours and the ability to perform some job duties remotely.

Primary Responsibilities

• Work closely with defense customers, other contractors, intelligence personnel, senior scientists, principal investigators, and program managers, to understand needs and develop or recommend solutions.

• Develop Automatic Target Recognition and Combat Identification (ATR/CID) algorithms and user interfaces using Python, MATLAB, and other languages for real world applications.

• Manage target knowledge databases and apply modeling and simulation techniques and tools to create or augment training data.

• Develop Machine Learning and Artificial Intelligence algorithms to classify images, discover and classify ESM data, or create efficiencies in other ATR/CID database processes.

• Leverage state-of-the-art AI/ML tools and methodologies to improve the performance of ATR/CID systems

• Write and present technical information related to development activities.

• Develop technical solutions and help write proposals for new work.

Basic Qualifications:

• Master’s degree in a science related degree field (Electrical Engineering, Computer Science, Physics, Engineering Physics, etc.) with 8+ years’ experience or a Doctoral Degree with 6+ years’ experience

• US citizenship

• Ability to obtain and maintain a TS/SCI clearance

• Adept in Python and MATLAB

• Proficient in Linux and Windows

• Pattern recognition and/or image classification experience

• Familiarity with common machine and deep learning packages such as Scikit-Learn, PyTorch, etc.

• Excellent communication skills and proven ability to work directly with customers and deliver results

• Mission oriented with a strong ability contribute to team goals and work in a team environment to deliver real world products

• Proficient with technical writing, documentation, and organization

• Robust sense of initiative, a self-starter who can work independently

• Basic understanding of electromagnetic phenomenology such as scattering, absorption, polarization, refraction, diffraction, etc.

Preferred Qualifications:

• Active SECRET clearance or higher, with an ability to obtain a TS/SCI clearance

• Experience with Combat Identification and Automatic Target Recognition algorithm development for air, ground, or space targets

• Experience working with monostatic or bi-static Synthetic Aperture Radar (SAR) and/or Synthetic Aperture Lidar (SAL) data and sensor systems

• Basic understanding of Computational Electromagnetics Prediction codes (Xpatch, SENTRi, CST, Feko, etc.)

• Understanding or experience with Electronic Support Measures (ESM)

• Understanding of DoD test processes

• Object Oriented Programing experience and/or Java and C++ experience

LInC

Electronic Warfare

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is a Fortune 500® technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, civil, and health markets. The company’s 45,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $14.4 billion for the fiscal year ended December 30, 2022.  For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here.

Securing Your Data

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Commitment to Diversity

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.