Radar Vision DL Engineer for Real-Time Edge Detection

Rotterdam Innovation City; Delft; On-site; EUR 90,000 - 125,000; Full time

Job summary

Robin Radar is seeking a Deep Learning Engineer to architect and implement object detection frameworks for non-natural radar imagery. You will work with AI specialists, software engineers, and radar experts to translate research into edge computing hardware powering live radar systems worldwide.

Responsibilities include designing robust 3D/4D/5D detection models, managing radar data labeling, and optimizing models with TensorRT for real-time edge inference.

Qualifications

• Master's degree in Computer Vision, AI, CS, or related field.
• 5+ years of deep learning experience in computer vision.
• Expertise in object detection, segmentation, and classification.
• Experience deploying models to edge hardware.
• Fluent English, written and spoken.

Responsibilities

• Framework design and architecture for robust detection, segmentation, and tracking models on complex radar data.
• Data strategy and labeling workflows for imperfect radar labels; automate dataset creation.
• Model optimization for edge devices using TensorRT for real-time inference.
• Collaborate with software and radar engineers to integrate DL models into live products.

Skills

Python

PyTorch

Edge computing

Object detection

Radar data familiarity

Education

Master's degree

Tools

TensorRT

Job description

Robin Radar is seeking a Deep Learning Engineer to architect and implement object detection frameworks for non-natural radar imagery. You will work with AI specialists, software engineers, and radar experts to translate research into edge computing hardware powering live radar systems worldwide.

Responsibilities include designing robust 3D/4D/5D detection models, managing radar data labeling, and optimizing models with TensorRT for real-time edge inference.