Design, develop, and optimize advanced computer vision and deep learning models for industrial applications such as defect detection, classification, and process control.
Apply state-of-the-art algorithms and continuously improve model performance through validation, tuning, and retraining.
Drive the transition of models from proof-of-concept to production-ready solutions. 2. Data Engineering & Pipeline Management
Own the end-to-end data lifecycle, including acquisition, annotation, preprocessing, and dataset management.
Ensure data robustness and quality under real industrial conditions (e.g., lighting, materials, positioning variability).
Collaborate on scalable data and deployment pipelines supporting efficient training and inference. 3. Industrial Deployment & System Integration
Deploy computer vision models into real-time industrial systems integrated with production lines and automation equipment.