Edge DL Engineer for Real-Time Radar Vision

Robin Radar

Delft

On-site

EUR 110,000 - 150,000

Full time

14 days+

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

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 deployments, powering live radar systems globally.

The role requires a Master’s in a related field, 5+ years in deep learning for computer vision, and strong Python/PyTorch skills.

Qualifications

Master's degree in Computer Vision, AI, CS or related field.
5+ years of professional experience in deep learning research for computer vision.
Proven expertise in object detection, segmentation, and classification models.
Deep familiarity with radar data or non-natural signal modalities like LiDAR, sonar, or medical imaging.
Hands-on experience deploying and optimizing models for edge computing hardware.
Advanced proficiency in Python and PyTorch.
Experience with TensorRT or similar high-performance inference libraries is a strong advantage.
Fluent English, both written and spoken.

Responsibilities

Framework design and architecture for detection, segmentation, and tracking on complex radar data.
Data strategy and label management for imperfect or missing radar labels; automate dataset creation.
Model optimization for edge: TensorRT-based real-time inference on edge hardware.
Cross-functional integration with software and radar engineers to deploy models into live products.