ROLE: Perception Engineer
📌Location: Detroit, Michigan, USA.
✅Pay Rate: $70/Hour
✅Eligibility: US Citizen & Green Card holder, GCAD, L2 EAD & H4 EAD
✅Work Type: On-site (W2 )
✅Employment Type: Contract
✅Joining Date: ASAP
✅Experience: 3+ years of experience in sensor calibration, multi-sensor fusion, or related domains, with strong foundation in linear algebra, 3D geometry, coordinate frames, quaternions, probability, Bayesian filtering, and data association.
✅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.
· Develop sensor calibration techniques (intrinsic and extrinsic) and coordinate transformations between sensors.
· Develop robust perception algorithms that maintain performance in adverse weather conditions such as rain, snow, fog, and low-light scenarios.
· 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 tracking.
· 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:
· 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 tracking 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).
