Senior AI Engineer (Sensing & Intelligence)

Your Mission

This position is responsible for designing, developing, fine-tuning, and optimizing deep learning models for quality inspection applications using 3D and wearable sensors. You will contribute to the development of advanced AI algorithms for sensing methodologies, object detection, recognition, segmentation, pose estimation, and human activity recognition across multiple modalities, including images, videos, and 3D/wearable sensor data.

What To Expect

• A strong interest in domains such as, but not limited to: 2D/3D object recognition, segmentation, pose estimation, feature extraction, and human activity recognition from multimodal data.
• Design, develop, and optimize deep learning models (e.g., convolutional neural networks, transformers) to process and analyze sensor data from various modalities (e.g., vision, depth) for quality inspection.
• Apply deep learning techniques for human activity recognition across video and other modalities.
• Evaluate and calibrate various sensors to ensure the collection of accurate data for training.
• Pre-process and prepare image and sensor data for effective model training, including data cleaning and augmentation.
• Validate the performance of implemented algorithms on real-world car part datasets.
• Document technical reports, program codes, and set-up manuals.

What You'll Bring

• A Master’s or Ph.D. degree in Electrical, Mechanical, or Computer Engineering, or a related discipline, with over 5 years of industry experience.
• Familiarity with object detection, recognition, and segmentation frameworks (e.g., YOLO, Faster R-CNN, Mask2Former).
• Experience with human detection and human activity recognition models (e.g., I3D, C3D).
• Experience with 3D sensor data from head-mounted cameras is a strong advantage.
• Proficiency in data preprocessing and augmentation techniques for images, videos, 3D point clouds, and wearable sensor data.
• Working knowledge of sensor methodologies, including data analysis, noise reduction, feature engineering, sensor calibration, and optimization strategies.
• Proven experience in developing and deploying deep learning models in real-world applications.
• Any patents, publications, specialist certifications, or awards in multimodal processing will be an added advantage.