Real-Time Radar Deep Learning Engineer (Edge Deploy)

Academic Key; Delft; A distancia; EUR 70.000 - 95.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Great Place to Work certified

Commuting allowance

30 days holiday leave

Training and certifications

High quality equipment

International team

Descripción de la vacante

Academic Key in Delft is seeking a Deep Learning Engineer to turn radar signal data into real-time detection models. You will design, train, and deploy neural networks that improve object detection and tracking on edge hardware.

Collaborating with AI, software, hardware and product teams, you will optimize models for noisy environments and field conditions, and contribute to robust radar systems deployed globally.

Formación

• MSc in Data Science, Computer Science, Artificial Intelligence, or a related field.
• 2–4 years of experience in Deep Learning, specifically in Computer Vision.
• Strong proficiency in Python and hands-on experience using PyTorch.
• Practical experience with edge deployment and model optimization tools like TensorRT or ONNX.
• Familiarity with non-natural signal modalities such as radar, sonar, LiDAR, or medical imaging.
• Fluent English, both written and spoken.
• A proactive mindset and strong problem-solving skills in a collaborative environment.

Responsabilidades

• Model design and architecture: Design, train, and optimize deep learning models for detection, segmentation, and classification. Tailor neural networks to process abstract, non-natural 3D, 4D, and 5D radar imagery.
• Target classification and tracking: Build advanced neural network architectures to detect and track small objects like birds and drones. Ensure models perform reliably despite real-world noise and weather.
• Data engineering and automation: Prepare, preprocess, and augment large-scale radar datasets for training pipelines. Implement automated labeling strategies to streamline data preparation at scale.
• Edge optimization and deployment: Optimize trained neural networks for high-performance inference on edge computing hardware. Collaborate with Software Developers and Radar Specialists to integrate models seamlessly into production systems.
• Research and field validation: Evaluate emerging deep learning techniques to continuously lift our radar capabilities. Test model robustness under diverse field conditions and document design choices clearly.

Conocimientos

Deep Learning

Computer Vision

Python

PyTorch

Edge Deployment

TensorRT/ONNX

Radar Signals

English Proficiency

Educación

MSc in Data Science/CS/AI or related

Herramientas

ONNX

TensorRT

Descripción del empleo

Academic Key in Delft is seeking a Deep Learning Engineer to turn radar signal data into real-time detection models. You will design, train, and deploy neural networks that improve object detection and tracking on edge hardware.

Collaborating with AI, software, hardware and product teams, you will optimize models for noisy environments and field conditions, and contribute to robust radar systems deployed globally.