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Responsibilities:

  • Design, build, and validate machine learning models for RF emitter identification, including feature engineering and training pipeline development.
  • Conduct hands-on exploratory data analysis on RF sensor datasets, characterizing feature distributions and producing documented findings.
  • Collaborate with the technical lead to investigate RF sensor data quality, attribution reliability, and feature behavior.

Requirements:

  • BS or MS in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related quantitative field; experience may be considered.
  • 5–7 years of hands-on applied experience in machine learning, data science, or RF signal processing.
  • Demonstrated proficiency in Python, PyTorch/TensorFlow, and Pandas/NumPy for ML and data science work.

Work Environment:

  • The role requires strong Python and deep learning skills and comfort with real-world noisy sensor data.
  • The ability to work in air-gapped Linux environments without cloud infrastructure or GPU acceleration is essential.

Global InfoTek, Inc.

Global InfoTek Inc. designs, develops, and deploys technologies that address national cyber and advanced technology needs. It is an established company with an award-winning track record spanning over two decades, operating with a focus on pioneering technologies and best business practices.

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