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Responsibilities:
- Designs, builds, and validates machine learning models for RF emitter identification.
- Conducts hands-on exploratory data analysis on RF sensor datasets using Python.
- Implements and maintains ML data pipelines on constrained edge hardware.
Required Skills:
- 5+ years of applied experience in machine learning or RF signal processing.
- Proficiency in Python, PyTorch/TensorFlow, and data manipulation libraries.
- Experience with real-world noisy sensor data and Linux environments.
Desired Skills:
- Familiarity with RF signal characteristics and passive receiver phenomenology.
- Experience with metric learning or similarity-learning architectures.
- Exposure to TDMA network protocols or military datalink systems.
Global InfoTek Inc.
Global InfoTek Inc. designs, develops, and deploys advanced cyber and technology solutions for national security needs. The company has been operating for over two decades with a focus on best-of-breed technologies.