AI/ML SME with Security Clearance

AI/ML Engineer SME
Location: Choice of Herndon, VA or Arlington, VA
Clearance Requirements: Active TS/SCI Clearance; the customer will sponsor a Full Scope Polygraph is candidate does not possess one already Description:
Signature Federal Systems is seeking a highly skilled AI/ML Machine Learning Engineer to join a cross-functional team of experts in research, data science, software development, physics, and mathematics.

As a key member of this team, you will leverage cutting-edge AI/ML tools and techniques to tackle the most complex challenges in Space – all in support of our national security. A perfect candidate would be both very familiar with AI/ML AND have experience with CNO development. This role offers a unique opportunity to collaborate with a diverse group of professionals, drive innovation, and contribute to the development of solutions that address critical problems in the Space domain.

The successful candidate will have advanced experience with and/or knowledge of: AI/ML, Deep Learning, or Computer Vision, modern software development practices/languages, and a passion for math and science.

Basic Qualifications

• Bachelor's degree in a STEM discipline (e.g. Electrical Engineering, Computer Science, Computer Engineering, Mathematics, Physics) or equivalent combination of education, training, and experience in a related technical field.
• Advanced experience in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, or Image Processing
• Experience with modern software development tools and practices
• TS/SCI clearance required to start

Desired Skills

• Advanced degree in a STEM discipline
• Proficiency in one or more of the following programming languages: Python, Java, C++, C#, or MATLAB
• Experience with TensorFlow, PyTorch, Keras, or Scikit-learn
• Experience with RF, SAR or EO image processing algorithms/techniques
• Experience with AWS or another cloud computing platform
• Excellent written and verbal communication skills
• Ability to work in a collaborative and team-based environment