Deep learning research engineer
Description
Rail Vision is a multidisciplinary company headquartered in Ra'anana. We are the leading provider of obstacle detection & classification systems in the railway industry around the globe, supporting Autonomous Train Operations. With our unique cognitive sensor fusion technology, based on advanced electro-optic sensors and deep learning, Rail Vision systems detect objects and obstacles on and along the tracks from up to 2 k”m away, in real-time, and in diverse weather and lighting conditions. We provide systems capable of operating in various environments: On mainline and high-speed rail, in urban environments, and in challenging switchyards. Rail Vision offers a range of complementary features based on collected and analysed data: Image-based Navigation, GIS Mapping and Predictive Maintenance. We’re looking for an experienced Deep Learning & Computer Vision research engineer to join our Algorithms group.
What will you do
Be a researcher of the core deep learning algorithms and partnering with other teammates. Developing our next generation 2D/3D perception models that utilizes CV in complex environment. Work across full ML cycle: data, design, train and debug, solvIng complex problems that aligned to customer KPIs.
Requirements
- Master’s degree in computer science, Engineering, or a related technical field or very experienced Bachelor.
- At least 6 years’ experience as a researcher engineer with deploying advanced algorithms.
- Understand deeply, train, and evaluate recent state-of-the-art algorithms in computer vision (e.g., object detection, semantic segmentation, self-supervised learning, vision transformers) for various domains.
- Experience in Python & PyTorch or other machine learning frameworks and mathematical modelling.
- Good communication skills, self-motivated, proactive, flexible and passionate about learning
- Focus on end to end delivery of solutions for real world scenario in challenging timeframe.
Every role in the library, ranked against your CV.
Rewritten from your real, matching experience for the job you pick.
Your whole pipeline in one place, with a fresh move every morning.