C++ Team Leader for Machine Learning & Computer Vision

Rail Vision is a multidisciplinary startup headquartered in Ra'anana. We are the leading provider of obstacle detection, collision avoidance and drive able areas 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 perception solution, Rail Vision systems detect obstacles on and along the tracks from up to 2 kilometers 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 analyzed data: Image-based Navigation, GIS Mapping and Predictive Maintenance.

We are looking for an experienced, creative with an exceptional mathematical thinking and highly motivated C++ Team Leader for Machine Learning & Computer Vision implantation, to join our top-notch software group.

In this position, you will lead a team of developers designing and implementing high-performance DSP, Image Processing, Deep Learning and Computer Vision algorithms, using the most advanced technology such as the newest Nvidia platforms, advanced C++, and modern development procedures and tools.

The team works intensively with the algorithms engineering teams, converting algorithms, and making them suitable to be used on real-time system.

Requirements:

Bachelor’s degree in a relevant technical discipline.
Experience in managing a software team.
At least 5 years' experience modern C++ (11 or newer).
Background with multithreaded programming.
Mathematics and algorithms oriented.
Excellent teamwork and human relations.
Independent, self-motivated, and fast learner.

Advantages:

Experience working in multidisciplinary environments.
Hands on experience with Python and Bash development.
Proven experience in image, Computer vision , Deep learning & Neural Networks
Familiarity with TensorRT framework.
Familiarity with OpenCV.
Familiarity with CUDA and NVIDIA platforms.