Radar DL Engineer: Real-Time Object Detection on Edge

Robin AI Limited; Delft; Hybrid; EUR 65,000 - 90,000; Full time

Benefits offered by this job

Pension plan

Commuting allowance

30 days paid holiday leave (plus 3)

Job summary

Robin Radar, a defence tech leader in radar, seeks a Deep Learning Engineer to design and deploy neural networks that detect small airborne objects in noisy environments. You will work with AI, software, hardware, and product teams to translate radar modalities into robust models.

The role focuses on 3D/4D/5D radar data, edge inference optimization, and field validation to ensure real-world performance and reliability. Fluent English and a proactive, collaborative mindset are essential.

Qualifications

• MSc in Data Science, Computer Science, AI or related field.
• 2–4 years of deep learning experience in computer vision.
• Proficiency in Python and PyTorch.
• Experience with edge deployment and model optimization tools like TensorRT or ONNX.
• Familiarity with radar/sonar/LiDAR or medical imaging modalities.
• Fluent English, written and spoken.
• Proactive, collaborative problem-solver in a team environment.

Responsibilities

• Design, train, and optimize deep learning models for detection, segmentation, and classification.
• Develop architectures to process radar imagery in 3D/4D/5D spaces.
• Prepare data pipelines and automate labeling for large radar datasets.
• Optimize models for edge hardware and integrate into production systems.
• Evaluate new DL techniques and validate robustness in field conditions.

Skills

Deep Learning

Computer Vision

Python

PyTorch

Edge deployment

Model optimization

Radar/Signal modalities

English proficiency

Proactive mindset

Education

MSc in Data Science, Computer Science, AI or related

Tools

TensorRT

ONNX

Job description

Robin Radar, a defence tech leader in radar, seeks a Deep Learning Engineer to design and deploy neural networks that detect small airborne objects in noisy environments. You will work with AI, software, hardware, and product teams to translate radar modalities into robust models.

The role focuses on 3D/4D/5D radar data, edge inference optimization, and field validation to ensure real-world performance and reliability. Fluent English and a proactive, collaborative mindset are essential.