Marathon TS is seeking a Radio Frequency focused Machine Learning Engineer with experience in computer vision and machine learning, along with exposure to Radio Frequency (RF) signals and systems, to develop advanced analytics and AI solutions. This role focuses on transforming complex visual and RF data—such as spectrograms, waterfall plots, IQ samples, and multi-modal sensor inputs—into actionable insights and mission-critical applications.
This is a fully onsite role in Colorado Springs, CO, and requires a secret clearance or higher.
The ideal candidate will combine traditional signal processing knowledge with modern machine learning techniques to solve challenging problems in image/video analysis and RF signal detection, classification, and interpretation in complex, real-world environments.
Key Responsibilities
- Develop, train, and deploy machine learning and computer vision models for detection, classification, tracking, and anomaly detection
- Analyze RF data (e.g., spectrograms, time-frequency representations, IQ samples) and apply ML techniques for signal classification and interpretation
- Build end-to-end data science pipelines, including data ingestion, preprocessing, feature engineering, model development, and deployment
- Apply multi-modal data fusion techniques combining RF and visual data for enhanced analytics and situational awareness
- Conduct experiments on large datasets using techniques such as data augmentation, transfer learning, and model optimization
- Collaborate with cross-functional teams (software, RF/hardware, and data engineering) to operationalize models
- Stay current with emerging techniques in machine learning, computer vision, and RF analytics
- Document methodologies, present findings, and support technical reporting or publications
- Optimize model performance in real-world conditions, including noisy RF environments and dynamic visual inputs
Required Qualifications
- Active Secret clearance (or higher) with ability to obtain TS/SCI
- Bachelor’s degree (or equivalent experience) in Computer Science, Electrical Engineering, Data Science, Applied Mathematics, Physics, or related field
- 3+ years of experience in data science, machine learning, or computer vision
- Strong programming skills in Python
- Experience with deep learning frameworks (PyTorch and/or TensorFlow/Keras)
- Understanding of signal processing fundamentals (e.g., Fourier transforms, filtering, modulation)
- Experience with computer vision tools (e.g., OpenCV, scikit-image)
- Experience building and deploying ML models (e.g., Docker, ONNX, TensorRT, or cloud platforms such as AWS, Azure, or GCP)
- Strong foundation in mathematics (linear algebra, probability/statistics, optimization)
Preferred Qualifications
- Experience applying ML to RF signals (e.g., signal classification, modulation recognition, spectrogram analysis)
- Experience with multi-sensor or sensor fusion systems
- Background in defense, aerospace, or wireless communications
- Familiarity with advanced ML techniques (e.g., transformers, self-supervised learning)
- Experience with real-time systems, edge AI, or embedded platforms (e.g., NVIDIA Jetson, FPGA)
- Experience working with large-scale datasets and distributed training (GPU/TPU environments)
