The hydrodynamic machine learning group in the Leidos Applied Science Division is looking for a Machine Learning Intern to support ongoing research in undersea acoustics. The intern(s) will be involved in undersea acoustic simulation, neural network design and evaluation efforts. 

Primary Responsibilities     

• Designing and generating training data using an acoustic simulator.

• Designing, training, and evaluating the performance of specialized neural network architectures.

Basic Qualifications

• Must be enrolled in Bachelor’s Degree program in Engineering, Physics, or Mathematics.

• Must be U.S. Citizen with the ability to obtain a DoD security clearance.

• Programming experience in Python, Tensorflow and Keras.

Preferred Qualifications

• Direct machine learning experience involving neural network design, training, and evaluation.

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.