Research Engineer – Generative AI and Computer Vision

About the role

The Research Engineer – Generative AI and Computer Vision will advance state‑of‑the‑art generative AI and deep‑learning methods for real‑world computer‑vision applications. You will work at the intersection of applied research and engineering, creating robust AI solutions for image understanding, synthetic data generation, visual inspection, and continuous model monitoring.

Key responsibilities

• Research, design, and implement generative AI techniques such as diffusion models, GANs, and image‑to‑image generation to produce realistic synthetic image datasets.
• Develop and evaluate deep‑learning models for industrial inspection tasks including classification, defect detection, anomaly detection, object detection, segmentation, and representation learning.
• Explore data‑efficient learning methods—transfer learning, self‑supervised learning, few‑shot learning, domain adaptation, active learning, and synthetic data augmentation—to reduce annotation effort.
• Build pipelines for continuous monitoring of deployed models, detecting data drift, changing image conditions, and performance degradation.
• Collaborate with cross‑functional teams to integrate AI solutions into production environments and ensure scalability.

Required profile

• Strong background in computer vision and generative AI research.
• Experience handling limited or imbalanced training data and addressing model‑performance issues in operation.
• Ability to translate novel research concepts into reliable, production‑ready solutions.

Required skills

• Generative AI
• Diffusion models
• Generative adversarial networks (GANs)
• Image‑to‑image generation
• Controllable generation
• Deep learning
• Convolutional Neural Networks (CNN)
• Transformer architectures
• Multimodal architectures
• Transfer learning
• Self‑supervised learning
• Few‑shot learning
• Domain adaptation
• Active learning
• Synthetic data augmentation
• Image classification
• Defect detection
• Anomaly detection
• Object detection
• Image segmentation
• Representation learning
• Model monitoring
• Data drift detection