Job description:
Our deep learning team drives the perception capabilities that enable autonomous vehicles to
understand and interact with the world. We’re seeking a motivated research scientist to develop
advanced algorithms and deep learning solutions for autonomous driving and ADAS applications,
leveraging both camera and lidar data. Your work will directly contribute to novel perception
systems and enable real-time, hardware-optimized performance on embedded platforms.
Responsibilities:
• Develop deep learning-based perception algorithms, including object detection, lane
detection, semantic segmentation, depth estimation, curb detection, etc.
• Design and evaluate cutting-edge network structures and training methods for vision tasks.
• Implement network compression and quantization-aware training to optimize models for
ASIC hardware deployment.
• Conduct prototype development, regression testing, benchmark testing, and performance
evaluation.
• Prepare demos to showcase model performance and deploy solutions on embedded platforms.
• Conduct R&D, stay updated with the latest research, and propose innovative ideas.
• Contribute to patent applications and publish research papers.
Qualifications:
• MS/PhD in Computer Science, Electrical Engineering, or a related field.
• 2+ years of experience in computer vision, machine learning, and deep learning
development.
• Proficiency in Python and C++ with hands-on programming skills; familiarity with embedded
systems is a plus.
• Experience with one or more of the following areas:
• Deep network development (visual data focus), object detection, tracking, and 3D
computer vision (stereo, optical flow, depth estimation).
• Structure from motion, network-based sensor fusion, and mathematical optimization.
• Familiarity with ADAS and autonomous driving technology, particularly in 3D object
detection and semantic segmentat
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