Autonomous Driving Vehicle Perception Engineer

Hi,
Greetings from Modern Agile Technologies.

Position:  Autonomous Driving Vehicle Perception Engineer

Location: Northville, MI (Onsite)

Type:       Contract

Experience: 4–10 Years

What You will Do:

•       Design and implement advanced perception algorithms for autonomous vehicles using LiDAR, cameras, radar, and GNSS.

•       Develop and optimize sensor fusion techniques to combine data from multiple sensors, improving the accuracy and reliability of perception systems.

•       Create algorithms for object detection, tracking, semantic segmentation, and classification from 3D point clouds (LiDAR) and camera data.

•       Work on Simultaneous Localization and Mapping (SLAM) algorithms, including Graph SLAM, LIO-SAM, and visual-inertial SLAM.

•       Develop sensor calibration techniques (intrinsic and extrinsic) and coordinate transformations between sensors.

•       Participate in real-time systems design and optimization to meet the high-performance requirements of autonomous driving.

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

•       Develop, test, and deploy machine learning models for perception tasks such as object detection and segmentation.

•       Collaborate with cross-functional teams, including software engineers, data scientists, and hardware teams, to deliver end-to-end solutions.

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

What You Will Bring:

•       Minimum 3+ years of experience in sensor calibration, multi-sensor fusion, or related domains.

•       Strong foundation in linear algebra, 3D geometry, coordinate frames, quaternions, probability, Bayesian filtering, and data association.

•       Hands-on experience with intrinsic and extrinsic calibration of LiDAR, cameras, and radar, including geometric calibration, coordinate transforms, and sensor synchronization.

•       Proven experience with perception algorithms for autonomous systems, particularly in the areas of LiDAR, camera, radar, GNSS, or other sensor modalities.

•       Deep understanding of LiDAR technology, point cloud data structures, and processing techniques; experience with PCL or Open3D.

•       Proficiency in sensor fusion for combining data from LiDAR, camera, radar, and GNSS, including handling time synchronization and motion distortion.

•       Solid background in computer vision techniques; experience with OpenCV and object detection models such as YOLO, Faster R-CNN, or SSD.

•       Experience with deep learning frameworks (TensorFlow or PyTorch) for object detection and segmentation tasks.

•       Hands-on experience with multi-object tracking algorithms such as SORT, DeepSORT, Kalman Filters, UKF, IMM, or JPDA.

•       Strong programming skills in C++ and Python; familiarity with geometric optimization libraries.

•       Familiarity with ROS2 for perception-based autonomous systems development.

•       Experience with parallel computing for real-time performance optimization (e.g., CUDA, OpenCL).