Computer Vision System Engineer
TXT e-Tech, a company belonging to the TXT Group, is looking for a Computer Vision Systems Engineer for the Aerospace & Aviation Business Unit. The person will be involved in the study, design and development of algorithms and functionalities for avionics systems, with particular attention to image processing, object recognition and tracking. Within a multidisciplinary team, they will work on algorithmic development, modeling, simulation and application of artificial intelligence and Computer Vision techniques. The role will also include the integration and verification of the developed solutions, deepening the connection between sensor data, algorithms and system performance. Main activities:
- Participation in the analysis of system functionalities and the definition of related algorithmic solutions;
- Study,
development and verification of target tracking algorithms, for estimating the motion of objects observed by sensors and maintaining their traces over time;
- Use and validation of simulation models and environments, also for the generation of infrared images;
- Development of software tools for the preparation and management of annotated image datasets, intended for Computer Vision applications;
- Development of methods and tools for evaluating performance and estimating the reliability of neural networks as a function of input data;
- Integration of tools and algorithms into the simulation environment, executi
- Participation in the analysis of system functionalities and the definition of related algorithmic solutions;
- Study,
development and verification of target tracking algorithms, for estimating the motion of objects observed by sensors and maintaining their traces over time;
- Use and validation of simulation models and environments, also for the generation of infrared images;
- Development of software tools for the preparation and management of annotated image datasets, intended for Computer Vision applications;
- Development of methods and tools for evaluating performance and estimating the reliability of neural networks as a function of input data;
- Integration of tools and algorithms into the simulation environment, executi