Deep Learning Engineer for Camera-LiDAR based Multimodal Perception (Automated Driving)

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

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.

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.

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