Autonomous Driving Vehicle Perception Engineer

What You will Do:

• Design and implement advancedperception algorithmsfor autonomous vehicles using LiDAR, cameras, radar, and GNSS.
• Develop and optimizesensor fusiontechniques to combine data from multiple sensors, improving the accuracy and reliability of perception systems.
• Create algorithms forobject detection, tracking, semantic segmentation, and classification from3D point clouds(LiDAR) and camera data.
• Work onSimultaneous Localization and Mapping (SLAM)algorithms, including Graph SLAM, LIO-SAM, and visual-inertial SLAM.
• Developsensor calibrationtechniques (intrinsic and extrinsic) and coordinate transformations between sensors.
• Participate inreal-time systems designand optimization to meet the high-performance requirements of autonomous driving.
• Work with ROS2 for integration and deployment ofperception algorithms.
• Develop, test, and deploymachine learning modelsfor perception tasks such asobject detectionand 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 insensor calibration,multi-sensor fusion, or related domains.
• Strong foundation inlinear algebra,3D geometry, coordinate frames, quaternions,probability,Bayesian filtering, anddata association.
• Hands-on experience with intrinsic and extrinsic calibration of LiDAR, cameras, and radar, including geometric calibration, coordinate transforms, and sensor synchronization.
• Proven experience withperception algorithmsfor 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 insensor fusionfor combining data from LiDAR, camera, radar, and GNSS, including handling time synchronization and motion distortion.
• Solid background incomputer vision techniques; experience with OpenCV andobject detectionmodels such as YOLO, Faster R-CNN, or SSD.
• Experience withdeep learning frameworks(TensorFlow or PyTorch) forobject detectionand 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 withgeometric optimizationlibraries.
• Familiarity with ROS2 for perception-based autonomous systems development.
• Experience with parallel computing for real-time performance optimization (e.g., CUDA, OpenCL).

Who We Are:
Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.
We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you.

The achievers and courageous challenge-crushers we seek, have the following characteristics and skills: