Key Responsibilities:
- Participate in research of advanced image/video processing algorithms using for autonomous driving, machine vision, and professional photography products.
- Research, design, and implement advanced perception algorithms in one or more of the following areas:
- 3D vision (stereo vision, structure-from-motion, SLAM, LiDAR-camera fusion, depth estimation)
- Vision-Language Models (VLMs) / Vision-Language Alignment (VLA)
- World models for robotics and autonomous driving perception & prediction
- Collaborate with cross-functional teams in sensor fusion, planning, and control to deliver end-to-end solutions.
- Publish research findings, file patents, and keep track of cutting-edge academic and industrial progress in the field.
- Contribute to scalable deployment of algorithms on embedded platforms.
Required Qualifications/Skills:
- PhD in Computer Science, Robotics, Electrical Engineering, or related field with a focus on computer vision, machine learning, or robotics perception.
- Basic knowledge in digital signal processing and AI based low-level computer vision approaches
- For deep learning projects, familiar with at least one deep learning framework such as tensorflow, pytorch, etc.
- Working knowledge of C/C++ and/or OpenCV.
- Familiarity with ASIC design approach and environment will be an advantage
- Research in image/video signal processing algorithms like noise removal, image enhancement, signal processing for digital cameras.
- Perform research into leading edge and emerging video technologies, ideas, approaches and keep up to date with new video processing standards and general industry trends
- Pruning, model optimization, and deployment of AI-based video/image processing algorithms on chipset.
- Machine vision-oriented video/image enhancement algorithm research and development
- C-model simulation for image/video signal processing algorithm development and verification.
- Ability to express ideas and communicate effectively.
- Any of the following skills and experiences would be an added advantage:
- Video algorithms for pre-processing, post-processing, video sharpening, temporal/spatial noise reduction, color consistency, etc.
- Key image processing algorithms for Camera Signal Processing cores
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