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ROLE: Computer Vision Perception Engineer (Autonomous Driving)

Location: Detroit, MI, USA.

Pay Rate: $75/Hour

Eligibility: US Citizen & Green Card holder, GCAD.

Work Type: On-site (W2 )

Employment Type: Contract

Joining Date: ASAP

Experience: At least 5 years of experience in Computer Vision Perception Engineer - Autonomous Driving, Strong expertise in computer vision and deep learning for object detection and segmentation tasks.

Job Description:

What You Will Do:

· Design and implement computer vision algorithms for object detection and segmentation using camera and LiDAR data fusion.

· Develop deep learning models for 2D and 3D object detection, including implementation and optimization of YOLO, Faster R-CNN, SSD, and transformer-based architectures.

· Create and optimize LiDAR point cloud processing pipelines using PCL and Open3D for 3D object detection and segmentation.

· Implement sensor fusion techniques to combine camera and LiDAR data for enhanced object detection accuracy.

· Develop instance and semantic segmentation algorithms using state-of-the-art models like Mask R-CNN, U-Net, and DeepLab.

· Implement and optimize deep learning models specifically designed for LiDAR point clouds, including PointNet, PointNet++, and other 3D neural network architectures.

· Develop robust perception algorithms that maintain performance in adverse weather conditions such as rain, snow, fog, and low-light scenarios.

· Build and maintain computer vision pipelines using OpenCV for image preprocessing, feature extraction, and geometric transformations.

· Design and implement multi-object tracking systems using Kalman filtering, SORT, and DeepSORT algorithms.

· Work with ROS2 for integration and deployment of perception algorithms.

· Optimize deep learning models for edge deployment and real-time inference performance.

· Develop robust evaluation metrics and testing frameworks for object detection systems.

· Collaborate with cross-functional teams to integrate perception algorithms into larger autonomous systems.

· Stay up-to-date with industry trends and emerging technologies to innovate and improve perception systems.

What You Will Bring:

· Strong expertise in computer vision and deep learning for object detection and segmentation tasks.

· Proficiency in deep learning frameworks (PyTorch and TensorFlow) with hands-on experience implementing detection models (YOLO, Faster R-CNN, SSD, RetinaNet, Detectron, etc.).

· Extensive experience with OpenCV for image processing and computer vision applications.

· Solid background in 3D perception using LiDAR point clouds; proficiency with PCL and Open3D libraries.

· Familiarity with LiDAR-specific deep learning models such as PointNet, PointNet++, VoxelNet, and other point cloud neural network architectures.

· Experience in developing and improving perception models for adverse weather conditions (rain, snow, fog) including domain adaptation and robust feature extraction techniques.

· Experience with sensor fusion techniques for combining camera and LiDAR data streams.

· Strong programming skills in Python and C++ for algorithm development and optimization.

· Experience with model optimization techniques for real-time inference.

· Familiarity with 3D geometry, coordinate transformations, and spatial data processing.

· Knowledge of evaluation metrics for object detection and tracking systems (mAP, IoU, custom metrics, etc.).