We are looking for a Deep Learning Engineer to build an automated image classification system for visual quality control in a manufacturing and e-commerce environment.
The system classifies product images into multiple quality and category labels, helping detect defective items and misclassified products before they reach customers.
The solution leverages convolutional neural networks and transfer learning to achieve high accuracy on visually diverse datasets.
Key Responsibilities
- Preprocess and normalize large image datasets
- Implement data augmentation to improve generalization
- Design and train CNN models for multi-class image classification
- Apply transfer learning using pre-trained architectures
- Compare baseline CNNs with advanced deep learning models
- Evaluate model performance and optimize architectures
- Prepare technical documentation and training reports
Requirements
- Strong background in Deep Learning and CNNs
- Experience with TensorFlow or PyTorch
- Knowledge of image preprocessing and augmentation techniques
- Understanding of transfer learning workflows
Nice to Have
- Experience with computer vision in e-commerce or manufacturing
- Knowledge of model optimization and performance tuning
- Familiarity with GPU training pipelines