Deep Learning Engineer
Core
Develop, optimize, and deploy neural networks to process radar signal data for real-time detection and tracking of small airborne objects like birds and drones in noisy environments.
Role type
Deep Learning Engineer (Computer Vision / Signal Processing)
Builds
Production radar detection and tracking models for edge computing hardware
Domain
Defense / Aviation / Infrastructure protection using radar signal processing
Deliverable
production ML models
Required skills
Deep Learning, Computer Vision, Python, PyTorch, Edge deployment optimization, Radar signal modalities
Preferred skills
TensorRT, ONNX, Non-natural signal modalities (sonar, LiDAR, medical imaging)
Technologies
PyTorch, TensorRT, ONNX
Responsibilities
Design and train deep learning models for detection, segmentation, and classification; Build neural networks to detect and track small objects; Prepare and augment large-scale radar datasets; Optimize models for high-performance inference on edge hardware; Evaluate emerging techniques and test model robustness in field conditions
Seniority
Mid-level, hands-on IC
