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Job Area:
Engineering Group, Engineering Group > Systems Engineering
We are looking for innovative and motivated individuals with strong background in advanced deep learning architectures for production grade L3 automated driving perception software. They shall develop scalable algorithms for Camera-LiDAR perception systems scalable to large scale data regimes (Petabytes). This includes fundamental understanding of computer vision, transformers, self-attention, cross attention in multi-modal sensor setup, volumetric occupancy, and volumetric flow. A global understanding of multi-senor calibration (camera-camera, camera-lidar) and related fusion frameworks is a necessity. A solid background in classical calibration is a big plus. They shall develop state of the art lidar and LiDAR-camera fusion deep learning models for complex urban and highway scenarios. Work closely with seasoned senior perception engineers in leading automated driving systems in OEMS & Robotaxi companies.
Minimum Qualifications:
PhD degree or equivalent in Engineering, Information Systems, Computer Science, or related field. PhD topic related with Camera/LiDAR based perception.
Masters with 3 - 15 years of industrial experience in the area of camera/lidar based perception with deep learning.
Preferred Qualifications:
Experience in deep learning for LiDAR perception, camera-LiDAR sensor fusion for DNN architectures and/or occupancy grid filtering.
Fundamental understanding of classical computer vision, multi-view geometry.
Proficient in advanced deep learning architectures transformers, cross-attention, Voxel/BEV grid-based feature representations for point cloud data.
3+ years of experience with Programming Language such as C++ and Python.
Experience working with, modifying, and creating advanced algorithms.
Analytical and scientific mindset, with the ability to solve complex problems.
Experience with robust software design for safety-critical systems.
Excellent written and verbal communication skills, ability to work with a cross-functional team.
Optional Qualifications/Experience
Classical Camera-LiDAR-RADAR offline/online calibration.
Classical or Deep learning-based Camera-LIDAR-RADAR fusion.
HD-maps fusion for perception.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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