Computer Vision Engineer

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Wabtec provides vision-based wayside detectors for the rolling stock maintenance market. Its non-contact measurement technology enables highly detailed condition assessment of train components—ranging from wheel surface condition to full train inspection—on trains operating in service and at high speeds. Wabtec's wayside systems and software applications and image analysis technology enable Train Operating Companies (TOCs) to manage fleet maintenance and operation through automatic measurements and inspections. Real-time alarms, alerts, and reports enable significant reductions in maintenance costs and increase fleet availability for revenue generation.

Role Overview

We are seeking a skilled Computer Vision Engineer to design, develop, and optimize advanced image processing and deep learning solutions for real-time applications. The role involves working on cutting-edge camera and laser-based systems for accurate measurement and detection, with a focus on innovation, performance optimization, and seamless integration into production environments.

Responsibilities

• Design, implement, and optimize computer vision algorithms using Python, MATLAB, and C++ for real-time performance
• Develop state-of-the-art solutions combining traditional image processing and deep learning for accurate rail component detection and measurement
• Research and apply new techniques in deep learning, unsupervised learning, and computer vision to enhance accuracy and efficiency
• Collaborate with cross-functional teams to integrate vision solutions into existing systems
• Conduct performance analysis, profiling, and optimization to meet high-speed processing requirements
• Develop prototypes and proof-of-concept projects to validate new technologies
• Stay current with emerging trends in AI, computer vision, and image processing, and contribute innovative ideas to the team
• Document methodologies, research findings, and code for knowledge sharing and reproducibility
• Participate in code reviews and contribute to team-wide technical discussion

Qualifications

Additional Information

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