Job Description
Computer Vision Perception Engineer (Autonomous Driving) Location: Detroit, Michigan, USA Work Mode: Onsite Start Date: Immediate Job Summary We are seeking a skilled Computer Vision Perception Engineer with strong experience in autonomous driving systems. The ideal candidate will have deep expertise in computer vision, LiDAR data processing, and deep learning for real-time object detection, segmentation, and tracking. Key Responsibilities Design and implement computer vision algorithms for object detection and segmentation using camera and LiDAR data. Develop and optimize deep learning models for 2D and 3D object detection (e.g., YOLO, Faster R-CNN, SSD, transformer-based models). Build and maintain LiDAR point cloud processing pipelines using tools such as PCL and Open3D. Implement sensor fusion techniques combining camera and LiDAR data for improved perception accuracy. Develop semantic and instance segmentation models (e.g., Mask R-CNN, U-Net, DeepLab). Create multi-object tracking systems using algorithms such as Kalman filtering, SORT, or DeepSORT. Optimize models for real-time inference and edge deployment. Work with ROS2 for integration and deployment of perception systems. Develop testing frameworks and evaluation metrics for performance validation. Collaborate with cross-functional teams to integrate perception modules into autonomous systems. Requirements Minimum of 5 years of experience in computer vision, preferably within autonomous driving or robotics. Strong expertise in deep learning for object detection and segmentation. Proficiency in Python and/or C++ for algorithm development. Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with OpenCV for image processing tasks. Strong understanding of LiDAR data and 3D perception techniques. Familiarity with sensor fusion approaches and real-time system constraints. Solid understanding of 3D geometry, coordinate transformations, and spatial data processing. Preferred Qualifications Experience with point cloud models such as PointNet, PointNet++, or VoxelNet. Knowledge of evaluation metrics such as mAP, IoU, and tracking performance metrics. Experience building systems that perform reliably in challenging conditions (e.g., low light, adverse weather). Familiarity with model optimization techniques for production deployment. Education Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Eligibility Applicants must be authorized to work in the United States. Job Type: Contract Pay: $75.00 per hour People with a criminal record are encouraged to apply Work Location: In person