Deep Learning Engineer – Radar AI

About the role

As a Deep Learning Engineer you will design, train and deploy neural networks that turn complex radar signal data into real‑time detection of small airborne objects. You will work closely with AI, software, hardware and product teams to bring cutting‑edge models into production and protect critical sites worldwide.

Key responsibilities

• Design, train and optimise deep learning models for detection, segmentation and classification of 3D‑5D radar imagery.
• Develop architectures to detect and track small objects such as birds and drones, ensuring robustness against noise and weather.
• Prepare, preprocess and augment large‑scale radar datasets, implementing automated labelling pipelines.
• Optimise models for edge inference using tools like TensorRT or ONNX and integrate them with production systems.
• Research emerging techniques, validate models in field conditions and document design decisions.

Required profile

• MSc in Data Science, Computer Science, Artificial Intelligence or a related technical field.
• 2‑4 years of deep‑learning experience, preferably in computer‑vision‑type applications.
• Fluent English communication skills.

Required skills

• Python programming.
• PyTorch deep‑learning framework.
• Model optimisation tools such as TensorRT or ONNX.
• Edge deployment and inference optimisation.
• Data preprocessing and augmentation for radar datasets.
• Understanding of non‑natural signal modalities (radar, sonar, LiDAR).

What we offer

• Great Place to Work® certified company with a comprehensive pension plan.
• Commuting allowance and 30 days paid holiday (plus the option to buy 3 extra days).
• Opportunities for training, certifications and skill development.
• High‑quality laptop/desktop, monitor, headphones and other necessary equipment.
• International team of 30+ nationalities with social events and Friday drinks.