Our client, a global innovation center in Singapore focused on research and development in advanced mobility ecosystems, driving smarter urban living solutions for broader societal benefits.
What to Expect
Work on deep learning for 2D/3D object recognition, segmentation, pose estimation, and human activity recognition.
Develop and optimize AI models (CNNs, transformers) for sensor data in quality inspection.
Apply deep learning to human activity recognition across video and other sensor types.
Calibrate sensors for accurate data collection and preprocess images/sensor data for training.
Test models on real-world car part datasets and document findings.
What You'll Bring
Master's/Ph.D. in Engineering or related field with 5+ years of experience.
Strong skills in object detection, segmentation (YOLO, Faster R-CNN, Mask2Former).
Experience with human detection/activity recognition models (I3D, C3D).
Bonus: Experience with 3D sensor data from head-mounted cameras.
Solid understanding of data preprocessing, sensor calibration, and deep learning deployment.
Extra points for patents, publications, or certifications in multimodal processing.