Computer Vision Engineer

Responsibilities

• Analyze existing image processing algorithms and propose technical improvements for cosmetics and dermatology applications
• Design and implement image preprocessing pipelines, including illumination correction, color normalization, and alignment
• Develop segmentation and measurement methods using both classical computer vision (OpenCV/SciPy) and deep learning
• Design, train, and evaluate deep learning models (e.g., U-Net, Mask R-CNN) for detecting skin features like pores, wrinkles, and pigmentation
• Manage training datasets, including annotation campaigns, labeling guidelines, and quality reviews
• Collaborate with cross-functional teams including subject matter experts, software developers, and hardware product teams
• Create internal tools, dashboards, and technical documentation to ensure reproducibility and traceability

Requirements

• Master's degree (Bac+5) or PhD in AI, Computer Vision, or Data Science
• 2 to 5 years of professional experience in the field
• Proficiency in Python and deep learning frameworks, specifically PyTorch
• Strong expertise in classical image processing techniques using OpenCV or SciPy
• Solid understanding of CNNs, Transformers, loss functions, and data augmentation strategies
• Fluency in French and English (B2-C1 level)

Preferred Qualifications

• Experience with GANs (Generative Adversarial Networks) for data augmentation
• Familiarity with MLOps tools, AzureML, or Docker
• Knowledge of deployment technologies such as ONNX, CUDA, and Edge computing

Benefits

• Opportunities for internal mobility and career evolution within an international group
• Convivial working environment
• Social benefits including works council (CE), profit-sharing schemes, and gift vouchers

About the Company

SGS is the world leader in inspection, verification, testing, and certification. With 95,000 employees and a network of over 2,400 offices and laboratories worldwide, SGS is the global benchmark for quality and integrity across numerous sectors, including cosmetics, pharmaceuticals, and consumer goods.