About the Company:

Rapiscan Systems is an industry leader in detection technology, providing cargo and vehicle inspection systems and services for ports, borders, military, high-threat facilities, and checkpoints to help customers combat terrorism, drug smuggling, illegal immigration, and trade fraud. We offer a broad array of scanning system configurations that leverage low-, medium-, and high-energy X-ray technology—or multiple X-ray technologies—to address each customer’s unique security application requirements. Our commitment to excellence in imaging performance, innovative design, and uncompromising quality ensures our solutions consistently deliver best-in-class imaging, high reliability, and operator satisfaction, to help customers find threats and contraband with ease and confidence.

About the Role:

Work as part of an expanding Science and Technology (S&T) team to drive forward the Research and Development Road Map for the Business. The data scientist role will have a focus on computer vision and deep learning to conduct novel research in object detection, image classification, and automated threat recognition (ATR). Candidate will work with a team of multi-disciplinary team of Scientists and Engineers to design new algorithms using emerging methodologies, improve performance of existing algorithms, and identify venues and unmet needs for new applications. The ideal candidate should be able to investigate, develop, prototype, and evaluate state-of-the-art algorithms in computer vision, deep learning, and image processing. The candidate should also be able to communicate research, document progress, and present results.

Responsibilities:

• Report to the Director of Science and Technology (S&T), Image Quality and AI and co-ordinate with other members of the S&T and engineering teams.
• Support and Contribute towards the establishment and implementation of the S&T RoadMap, with the aim of developing and protecting differentiated technologies to integrate into products and aid sales.
• Work as a member of the wider S&T team, designing, planning, performing, documenting, and interpreting scientific data within the scope of the Science and Technology RoadMap.

Qualifications:

• Master’s degree in Electrical Engineering, Computer Science, or related technical discipline.
• Focus on computer vision, machine learning/deep learning, or image processing is preferred.
• Experience in Python, C/C++, and Matlab.
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
• Strong debugging and problem-solving skills.
• Track record in applying computer vision and machine learning techniques to object detection, recognition, or segmentation through academic research or industry projects.
• Understanding of image processing techniques such as filtering, feature extraction, image enhancement, image registration, and edge detection.
• Familiarity with popular deep learning architectures for computer vision such as ResNet, RetinaNet, or VGGNet.
• Knowledge on data augmentation techniques for small datasets.
• Must be a team-player, organized, and self-motivated.
• Strong verbal and written communication skills.
• Some travel to customer or other Rapiscan sites is expected, usually below 10% of the time.