Deep Learning Algorithm Engineer

About Company & Role

neuRay Labs is an innovative company in the worlds of AI and sensor fusion, especially of radar & electro-optics sensors. Our goal is to revolutionize radar signal processing schemes in AI by leveraging visual information in order to obtain never seen before performance.

As an algorithm engineer, you will work with other professionals like yourself to solve challenging problems and realize novel idea into products that meets user’s needs. The ideal candidate would be up to date with state-of-the-art research and able to devise further improvements while being a hands-on engineer with extraordinary coding skills.

What You'll Do

• Image, video and radar processing algorithm research and development from the initial stages of research and through all stages of product development.
• Develop algorithms for perception, spatial understanding, and autonomous decision-making capabilities using deep neural networks and classical computer-vision and radar algorithms.
• Complete system engineering for specific needs, Integrating many algorithms together, and end-to-end performance optimization.

Qualifications

• MSc/PhD Computer Science/ Electrical Engineering/ Mathematics/ Physics or similar.
• Minimum of 3 years in research and development of Deep Learning algorithms for computer vision or radar signals.
• Strong software engineering skills and experience in the complete process of development - design, implementation, deployment.
• Proven experience with Python and AI & CV libraries such as pytorch, tensorflow, opencv, scikit-learn.
• Proven experience building ML/DL solutions in production.
• Proactive, can-do attitude and self-management skills.
• Excellent verbal communication skills, problem solving skills and attention to details.

Advantages

• Experience with deploying Deep Learning algorithms on edge devices, for example using NVIDIA TensorRT or other deep learning inference optimization libraries.
• Practical experience using C++ or MATLAB.
• Experience with cloud providers (e.g. AWS, gcloud, Azure).