Overview
In this role you will contribute to TrainScanner, a leading railway inspection platform using 3D scanning, computer vision, and automated analysis. You collaborate with cross-functional teams to enhance railway safety through accurate digital reconstruction and intelligent inspection algorithms. Expect to tackle challenging problems in calibration, data processing, and 3D model analysis that scale in industrial environments. This is a mission-driven opportunity to shape the future of mobility with advanced perception tech.
Compensaciones / Ventajas stability and long-term career
collaborative environment
opportunity to work on innovative projects
investment in development and award-winning learning
competitive social coverage
dynamic reward package
Responsabilidades Define and select cameras, optics and lighting systems for railway inspection applications
Develop calibration strategies and optimize image acquisition processes
Process and reconstruct data from 3D cameras, laser sensors and other scanning technologies




Design and develop computer vision algorithms for automated inspection and measurement systems
Create solutions for point cloud filtering, segmentation, cleaning and 3D model analysis
Collaborate with multidisciplinary teams to deploy innovative inspection architectures in industrial environments
Requisitos principales Degree in Computer Science, Engineering, Physics, Mathematics or a related field
Experience in industrial computer vision and 3D reconstruction projects
Strong knowledge of camera calibration, point cloud processing, computational geometry and dimensional measurement algorithms
Professional programming experience with C++ and Python
Hands-on experience with MVTec HALCON and industrial imaging systems
Knowledge of optics, cameras, lenses and lighting technologies
Familiarity with Git, GitLab, CI/CD practices and Agile development methodologies
Strong analytical mindset, autonomy and problem-solving skills
Analytical mindset
Auton

📌 Computer vision engineer (Barcelona)
🏢 Alstom
📍 Barcelona