Haifa
Full time
Mobileye is the world leader in automotive and driving assistance systems, developing the world's most advanced software technologies and hardware architectures. Our team in Haifa develops cutting-edge technologies to deploy deep learning and computer vision algorithms efficiently on the Mobileye platform. Our work contributes to saving lives and advancing the capabilities of autonomous vehicles. Check out our technology in action: https://www.youtube.com/watch?v=50NPqEla0CQ We are looking for a deep learning software engineer to join the Mobileye Autonomous Driving software group in Haifa, focusing on Deep Learning optimizations. This role offers an exciting opportunity to collaborate with highly talented engineers, contribute to an innovative product, and work with cutting-edge AI technologies.
What will your job look like:
- Develop a software product that optimizes deep learning networks. The optimizations include learnable techniques such as quantization, pruning and compression. This software product is the initial stage of the deep learning inference flow and is essential for enabling Mobileye’s deep learning networks to operate efficiently on low-power hardware within vehicles.
- Development is mostly in Python programming language, using deep learning frameworks such as Pytorch.
- Collaborate closely with Mobileye’s algorithm teams to ensure the fast and accurate deployment of their state-of-the-art models.
- The work encompasses the entire software development cycle, including code implementation, unit testing, CI/CD processes, and more.
- Literature research and POC implementation of new optimization algorithms.
- Your work will position you at the forefront of machine learning optimizations.
All you need is:
- BSc/MSc in Computer Science/ Electrical Engineering with computer science chain.
- Knowledge in Python/C/C++.
- Knowledge in CI/CD pipelines and containerized environments – advantage.
- Background in Neural Networks/Deep Learning – advantage.
- Experience in Pytorch – advantage.
