we are a global leader in autonomous driving technologies and advanced driver-assistance systems (ADAS). Our cutting-edge solutions, including the EyeQ chip, company SuperVision, company Drive, and company Chauffeur, leverage computer vision and machine learning to enhance vehicle safety and enable self-driving capabilities. Integrated into millions of vehicles worldwide, our technology is redefining the automotive industry and driving the evolution towards smarter, safer, and more autonomous mobility.
In our group, we research, develop, and deploy state-of-the-art lidar based techniques to achieve world-class results, enabling the safe development of Autonomous Driving features and Advanced Driver Assistance Systems.
What will your job look like:
Research, design, develop, and implement lidar based algorithms in both Python and C++ for solving complex problems
Evaluate existing models and techniques, and propose innovative approaches to improve algorithm performance and accuracy
Examine your algorithms on large-scale real-world data from our data collection vehicles across the globe
Collaborate with cross-functional teams to understand requirements and develop solutions
Optimize existing algorithms to improve performance and scalability.
Requirements: M.Sc./Ph.D. in Computer Science, Electrical Engineering or a related field, with research in deep neural networks
3+ years of experience in developing Computer Vision algorithms employing deep neural network techniques
Knowledge of transformers and specifically Vision Transformers is an advantage
Strong statistical analysis, mathematical, and problem-solving skills
Ability to learn new technologies and techniques
Independence, creativity and a proactive approach
Experience with the automotive industry is an advantage.
This position is open to all candidates.