Senior RF ML Research Scientist (Poly-Cleared)

Peraton; Maryland; On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Increased sign-on bonus eligibility

Job summary

Peraton is looking for a Senior Research Scientist to support R&D efforts focused on RF Machine Learning and signal processing, based in Maryland. This role involves leading the design and development of algorithms for wireless communications.

The ideal candidate should have significant experience in machine learning frameworks and a deep understanding of RF and signal processing. A full-time commitment is required at a customer site near College Park, MD.

This position may offer an increased sign-on bonus depending on eligibility.

Qualifications

• Minimum of 6+ years of experience in a relevant field.
• Strong experience in RF Machine Learning, digital signal processing, or wireless communications.
• Proficiency in Python and at least one additional programming language.

Responsibilities

• Lead the design and development of RF/ML algorithms for communications applications.
• Implement machine learning for RF signal detection and classification.
• Develop software prototypes using Python and C/C++.

Skills

Radio frequency Machine Learning

digital signal processing

wireless communications

programming in Python

machine learning frameworks

Education

Bachelor’s degree in related field

Master’s degree in related field

Ph.D. in related field

Tools

PyTorch

TensorFlow

Keras

scikit-learn

GNU Radio

Job description

Peraton is looking for a Senior Research Scientist to support R&D efforts focused on RF Machine Learning and signal processing, based in Maryland. This role involves leading the design and development of algorithms for wireless communications.

The ideal candidate should have significant experience in machine learning frameworks and a deep understanding of RF and signal processing. A full-time commitment is required at a customer site near College Park, MD.

This position may offer an increased sign-on bonus depending on eligibility.