Biometrics and AI Research Scientist

Location

Pasadena, United States of America

Thales people architect identity management and data protection solutions at the heart of digital security. Business and governments rely on us to bring trust to the billions of digital interactions they have with people. Our technologies and services help banks exchange funds, people cross borders, energy become smarter and much more. More than 30,000 organizations already rely on us to verify the identities of people and things, grant access to digital services, analyze vast quantities of information and encrypt data to make the connected world more secure.

Biometrics and AI Research Scientist

Pasadena, CA - Hybrid

Must be a U.S. Person as defined in applicable law, or otherwise authorized or eligible for authorization, to access hardware, software, technology or technical data controlled under the Export Administration Regulations (EAR).

Applicants must be legally authorized to work in the United States for any employer at the time of hire. This position is not eligible for visa sponsorship or for assuming sponsorship of an employment visa now or in the future.

Thales is looking for a Biometrics and AI Research Scientist in our Pasadena, California-based biometric algorithms team who will lead and conduct applied research towards the implementation and improvement of the algorithms underlying our world-class biometric product line. Research areas include biometric image quality assessment, finger friction ridge, face, iris and scars/marks/tattoo recognition, biometric fusion, and presentation attack detection.

• Develop state-of-the-art biometric algorithms and systems for image quality assessment, recognition, fusion, and presentation attack detection
• Evaluate and continuously improve these algorithms for biometric performance, speed, and demographic equitability
• Validate each improvement after system integration and for the targeted scenario
• Stay abreast of the latest scientific publications in biometrics and pertinent fields of computer vision (CV)
• Implement and evaluate published approaches to benchmark them against our own
• Propose new approaches for features that differentiate us from the competition
• Write near-production level code and practice secure coding standards
• Collaborate closely with your team members while effectively using resources within the global organization
• Grow into the role of a Thales-wide subject matter expert in your fields of specialization
• Prepare submissions for internal and external technology evaluations
• Occasionally support pre/post-sales projects
• Secure IP by submitting patent applications
• Shape research roadmaps in negotiations with product managers and business owners

• A Master’s of Science with 3 years of experience in a relevant and technical discipline or a PhD in Electrical Engineering, Computer Science, or a related field
• First-authored publications in related conference or journal if you possess a PhD
• At least 3 years of recent (in the last 5 years) hands on coding skills experience in C/C++ and Python in a corporate and/or academic setting
• Recent hands-on experience in designing, training, and deploying deep neural networks using PyTorch, Tensorflow, Onnxruntime or Open Vino
• Prior completed-project experience in at least one of the fields: biometrics, 2D or 3D object detection & recognition, pose estimation, segmentation and texture analysis/synthesis
• Experience in classical and deep-learning-based machine learning for CV applications
• A thorough understanding of digital image processing
• Prior experience in an analytical role using scientific rigor to create solutions
• Background in stochastic signal analysis and detection, as relevant to these field
• Ability to effortlessly switch between the big-picture and detailed view of a problem

• Extensive knowledge of deep learning on image processing including convolutional neural network, transformer neural network, graph neural network
• Experience in GPU programming using CUDA or OpenCL
• Experience in developing algorithms for…