Position Overview:

As the Research Scientist, you will be responsible for developing cutting-edge deep learning-based perception algorithms for enhancing the perception capabilities of our autonomous driving systems.

Responsibilities:

• Design and implement state-of-the-art deep neural network architectures and training methodologies for addressing complex perception tasks, such as object detection, lane detection, and segmentation.
• Develop algorithms for depth estimation, stereo vision, optical flow, and other tasks related to spatial understanding in ADAS.
• Investigate and develop strategies for compressing deep neural networks while maintaining performance, particularly for hardware acceleration on ASIC platforms.
• Optimize and fine-tune network structures to meet real-time performance requirements on embedded systems.
• Stay at the forefront of deep learning and computer vision research by continuously reviewing and implementing state-of-the-art techniques.
• Propose and explore novel ideas and approaches to advance the capabilities of perception algorithms in ADAS.
• Contribute to patent applications and research papers, showcasing the innovative solutions developed during your tenure.

Qualification/ Requirements:

• Master's or Ph.D. in Computer Science, Robotics, AI or related.
• Proven research and development experience in deep learning and computer vision, with a focus on perception tasks.
• Strong expertise in designing, training, and evaluating deep neural networks for visual data analysis.
• Proficiency in one or more of the following areas: object detection and tracking, stereo vision, depth estimation, multi-view geometry, 3D computer vision, structure from motion, network compression, and optimization.
• Advanced programming skills in Python, with familiarity in C++ being a plus.
• Strong mathematical foundation in optimization techniques relevant to computer vision and deep learning.