Skill

Convolutional Neural Networks (CNN)

Data Science, Analytics and AI/ML

Convolutional Neural Networks (CNNs) are a class of deep learning models that use layers of learnable filters (convolutions) to automatically detect spatial patterns like edges, textures, and shapes in data, most commonly images. They are widely used by machine learning engineers and researchers for tasks such as image classification, object detection, facial recognition, and medical image analysis. CNNs underpin many computer vision applications, including those in autonomous vehicles and photo-tagging software.

Open roles requiring Convolutional Neural Networks (CNN) (1)

Principal Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles

NVIDIA

$272,000 – $431,250

NVIDIA is hiring a principal-level perception engineer to lead the design and deployment of 3D obstacle detection systems for autonomous vehicles, working across deep learning architecture, model optimization, and cross-functional coordination. This role suits someone with 15+ years shipping production perception systems who can balance hands-on technical work with mentoring and setting strategic direction.

Listed on NVIDIA’s careers site · Apply there ↗

Roles that use Convolutional Neural Networks (CNN)

• Software Engineer1

• TensorFlow
• PyTorch
• Deep Learning
• Computer Vision
• Object Detection