Calibration Engineer – Self-Driving
On-siteHanoi, Hanoi, Vietnam or Ha Noi, Ninh Binh, Socialist Republic of Vietnam
Job Summary
Develop and optimize algorithms for 3D object detection, multi-object tracking, and semantic segmentation using multi-sensor data including camera, LiDAR, and radar. Design foundation models for self-driving perception and build multi-sensor fusion pipelines to enhance robustness under diverse driving scenarios. Research and implement state-of-the-art methods in machine learning and computer vision, such as BEV perception and occupancy networks, while translating insights into production-ready solutions. Optimize deep learning models for real-time inference on automotive-grade hardware and execute evaluation across real-world datasets and simulation environments. Collaborate with cross-functional teams to integrate perception models into the full self-driving stack and contribute to data curation and scalable training pipelines. Drive engineering excellence through high-quality, efficient code and stay current with advances in computer vision and robotics.
Required Qualifications
- MSc/PhD in Computer Science, Electrical Engineering, Robotics, or a related field
- 3+ years of relevant industry experience
- Experience with OpenCV in Python and C++
- Knowledge of sensor alignment and calibration including camera, IMU self-calibration, Lidar-camera calibration, radar-camera calibration
- Experience with Kannala, Scaramuzza algorithms
- Experience with multiple cameras synchronization
- Experience with solving software problems using geometry and linear algebra
- Experience in handling 3D point cloud data
- Knowledge of multi-sensor calibration and fusion techniques
- Strong software engineering skills with emphasis on scalability, reliability, and performance optimization
- You agree that you have read VinFast's Personal Data Protection Policy and consent for VinFast to process your personal data in accordance with the Policy and the applicable regulations on personal data protection
Desired Qualifications
- Experience with autonomous driving or ADAS perception systems
- Background in SLAM, 3D reconstruction, occupancy networks, or sensor simulation
- Track record of publications in top-tier conferences
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